diff --git a/Fictional Character Battle Outcome Prediction/Dataset/fictional_character_battles_complex.csv b/Fictional Character Battle Outcome Prediction/Dataset/fictional_character_battles_complex.csv new file mode 100644 index 000000000..2bf6654b3 --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/Dataset/fictional_character_battles_complex.csv @@ -0,0 +1,2352 @@ +Character,Universe,Strength,Speed,Intelligence,SpecialAbilities,Weaknesses,BattleOutcome +Wonder Woman,Marvel,7,8,3,Telekinesis,Kryptonite,0 +Iron Man,Marvel,4,7,9,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,8,7,5,Telekinesis,Magic,0 +Spider-Man,DC Comics,5,6,10,Telekinesis,Kryptonite,0 +Flash,Marvel,7,6,2,Invisibility,Magic,0 +Spider-Man,DC Comics,10,9,7,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,3,6,2,Super Strength,Silver,1 +Thor,DC Comics,7,2,4,Invisibility,Magic,1 +Batman,DC Comics,8,2,7,Flight,Silver,0 +Iron Man,DC Comics,5,5,4,Flight,Wooden Stake,0 +Superman,DC Comics,4,4,7,Telekinesis,Kryptonite,0 +Thor,DC Comics,8,2,7,Flight,Wooden Stake,0 +Iron Man,DC Comics,8,3,1,Super Strength,Silver,0 +Batman,Marvel,3,7,6,Invisibility,Wooden Stake,0 +Flash,DC Comics,6,8,9,Invisibility,Kryptonite,0 +Superman,Marvel,5,6,2,Invisibility,Wooden Stake,0 +Iron Man,Marvel,2,5,3,Flight,Kryptonite,0 +Captain America,Marvel,8,1,10,Invisibility,Magic,1 +Wonder Woman,Marvel,6,8,5,Telekinesis,Silver,1 +Thor,Marvel,2,3,9,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,5,6,4,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,1,3,1,Flight,Wooden Stake,0 +Iron Man,DC Comics,10,7,4,Invisibility,Magic,1 +Superman,DC Comics,6,7,6,Flight,Kryptonite,0 +Superman,Marvel,9,9,5,Invisibility,Magic,0 +Thor,Marvel,1,5,1,Super Strength,Magic,0 +Thor,Marvel,10,8,4,Super Strength,Wooden Stake,1 +Wonder Woman,DC Comics,3,10,6,Flight,Kryptonite,0 +Superman,DC Comics,7,10,10,Telekinesis,Wooden Stake,1 +Superman,DC Comics,4,8,10,Flight,Silver,0 +Superman,Marvel,9,1,4,Telekinesis,Silver,0 +Iron Man,Marvel,3,5,9,Invisibility,Kryptonite,0 +Superman,Marvel,5,3,5,Telekinesis,Magic,0 +Spider-Man,DC Comics,3,1,8,Telekinesis,Kryptonite,0 +Superman,Marvel,7,4,9,Invisibility,Kryptonite,0 +Spider-Man,Marvel,5,8,10,Super Strength,Silver,1 +Iron Man,Marvel,9,3,5,Invisibility,Silver,0 +Thor,Marvel,7,10,6,Flight,Magic,1 +Flash,DC Comics,2,2,1,Flight,Magic,0 +Spider-Man,DC Comics,4,9,7,Flight,Kryptonite,0 +Iron Man,Marvel,9,10,4,Flight,Wooden Stake,0 +Flash,Marvel,2,5,2,Flight,Kryptonite,0 +Flash,DC Comics,10,7,5,Super Strength,Magic,1 +Superman,DC Comics,9,2,3,Super Strength,Wooden Stake,0 +Iron Man,Marvel,10,9,6,Telekinesis,Silver,1 +Flash,DC Comics,5,9,8,Flight,Magic,0 +Superman,DC Comics,2,4,7,Invisibility,Magic,0 +Wonder Woman,Marvel,4,4,3,Flight,Wooden Stake,0 +Iron Man,DC Comics,7,6,8,Super Strength,Magic,0 +Flash,DC Comics,8,10,2,Flight,Magic,0 +Thor,DC Comics,3,10,10,Super Strength,Magic,1 +Spider-Man,DC Comics,1,10,9,Telekinesis,Magic,0 +Wonder Woman,Marvel,4,6,4,Telekinesis,Magic,0 +Thor,DC Comics,2,1,1,Telekinesis,Magic,0 +Captain America,DC Comics,8,9,8,Super Strength,Magic,1 +Superman,Marvel,4,2,7,Flight,Magic,0 +Flash,DC Comics,2,5,5,Flight,Silver,0 +Spider-Man,Marvel,6,9,10,Invisibility,Magic,1 +Thor,Marvel,6,4,5,Super Strength,Silver,1 +Spider-Man,DC Comics,10,3,7,Invisibility,Silver,1 +Captain America,DC Comics,4,7,5,Telekinesis,Kryptonite,0 +Batman,DC Comics,6,6,8,Flight,Kryptonite,0 +Superman,DC Comics,2,8,6,Super Strength,Silver,1 +Superman,DC Comics,10,3,5,Invisibility,Silver,0 +Iron Man,Marvel,2,5,9,Invisibility,Magic,1 +Flash,DC Comics,10,10,2,Invisibility,Kryptonite,0 +Superman,Marvel,4,4,1,Flight,Wooden Stake,0 +Superman,DC Comics,8,4,8,Flight,Kryptonite,0 +Thor,Marvel,7,4,3,Flight,Silver,1 +Wonder Woman,DC Comics,9,10,7,Super Strength,Silver,1 +Superman,DC Comics,8,8,10,Flight,Magic,1 +Superman,DC Comics,5,6,8,Super Strength,Magic,1 +Flash,DC Comics,2,3,6,Invisibility,Kryptonite,0 +Captain America,DC Comics,5,10,10,Invisibility,Magic,1 +Wonder Woman,Marvel,8,5,9,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,10,6,7,Flight,Wooden Stake,1 +Flash,DC Comics,9,5,10,Invisibility,Magic,1 +Spider-Man,DC Comics,9,6,5,Flight,Wooden Stake,1 +Spider-Man,Marvel,1,8,8,Super Strength,Wooden Stake,0 +Superman,DC Comics,9,7,2,Invisibility,Kryptonite,0 +Superman,Marvel,7,5,7,Flight,Wooden Stake,0 +Iron Man,DC Comics,9,10,4,Invisibility,Silver,1 +Spider-Man,Marvel,8,6,9,Invisibility,Silver,1 +Thor,DC Comics,1,4,1,Flight,Kryptonite,0 +Superman,DC Comics,8,9,7,Invisibility,Magic,1 +Thor,Marvel,8,4,6,Invisibility,Kryptonite,0 +Superman,DC Comics,3,1,8,Invisibility,Magic,0 +Flash,Marvel,1,7,5,Invisibility,Magic,0 +Thor,DC Comics,8,7,1,Super Strength,Magic,0 +Batman,DC Comics,3,4,1,Invisibility,Magic,0 +Thor,Marvel,3,3,9,Telekinesis,Magic,0 +Wonder Woman,DC Comics,1,8,10,Invisibility,Kryptonite,1 +Spider-Man,Marvel,5,5,6,Flight,Magic,0 +Superman,Marvel,10,10,10,Telekinesis,Wooden Stake,1 +Spider-Man,DC Comics,7,7,5,Super Strength,Wooden Stake,1 +Wonder Woman,DC Comics,10,4,1,Telekinesis,Magic,0 +Wonder Woman,DC Comics,9,4,6,Telekinesis,Wooden Stake,0 +Thor,Marvel,7,8,6,Telekinesis,Silver,1 +Captain America,Marvel,9,8,3,Flight,Kryptonite,0 +Captain America,DC Comics,8,2,8,Flight,Kryptonite,0 +Wonder Woman,Marvel,2,2,1,Flight,Magic,0 +Captain America,Marvel,1,3,1,Super Strength,Magic,0 +Superman,Marvel,7,3,6,Flight,Silver,0 +Iron Man,Marvel,7,1,10,Flight,Magic,0 +Batman,DC Comics,8,3,1,Telekinesis,Wooden Stake,0 +Thor,DC Comics,5,6,6,Flight,Silver,0 +Iron Man,DC Comics,3,8,1,Invisibility,Wooden Stake,0 +Captain America,Marvel,8,10,6,Flight,Kryptonite,1 +Thor,Marvel,6,6,3,Super Strength,Wooden Stake,1 +Iron Man,Marvel,3,5,8,Super Strength,Kryptonite,0 +Spider-Man,Marvel,1,4,6,Invisibility,Wooden Stake,0 +Captain America,DC Comics,3,3,1,Super Strength,Kryptonite,0 +Flash,Marvel,5,4,5,Super Strength,Magic,0 +Iron Man,Marvel,3,7,8,Telekinesis,Wooden Stake,0 +Flash,DC Comics,1,1,3,Invisibility,Kryptonite,0 +Superman,DC Comics,5,7,6,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,10,1,5,Telekinesis,Silver,0 +Captain America,Marvel,7,2,6,Flight,Magic,0 +Batman,Marvel,7,4,10,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,9,1,1,Flight,Silver,0 +Captain America,Marvel,10,9,7,Flight,Wooden Stake,1 +Flash,Marvel,10,6,9,Telekinesis,Silver,0 +Superman,Marvel,3,1,2,Super Strength,Wooden Stake,0 +Batman,DC Comics,7,1,10,Invisibility,Magic,1 +Batman,Marvel,1,6,5,Super Strength,Silver,0 +Batman,DC Comics,4,4,10,Telekinesis,Magic,0 +Thor,DC Comics,4,4,4,Telekinesis,Kryptonite,0 +Thor,DC Comics,5,6,6,Telekinesis,Wooden Stake,0 +Flash,Marvel,7,7,6,Telekinesis,Wooden Stake,1 +Wonder Woman,Marvel,7,9,2,Telekinesis,Magic,1 +Batman,DC Comics,4,10,2,Telekinesis,Magic,0 +Wonder Woman,Marvel,7,5,4,Super Strength,Kryptonite,0 +Spider-Man,Marvel,3,9,1,Flight,Silver,0 +Batman,DC Comics,6,4,9,Super Strength,Wooden Stake,1 +Iron Man,Marvel,2,10,7,Invisibility,Wooden Stake,0 +Batman,Marvel,10,2,7,Super Strength,Kryptonite,0 +Flash,Marvel,9,3,3,Telekinesis,Kryptonite,0 +Thor,Marvel,5,1,3,Super Strength,Magic,0 +Thor,DC Comics,6,6,1,Flight,Magic,0 +Iron Man,DC Comics,4,6,3,Invisibility,Silver,0 +Iron Man,Marvel,10,1,3,Super Strength,Kryptonite,0 +Captain America,Marvel,7,3,4,Flight,Silver,0 +Spider-Man,Marvel,9,5,4,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,7,3,3,Invisibility,Wooden Stake,1 +Flash,Marvel,1,10,10,Super Strength,Kryptonite,1 +Flash,Marvel,1,3,8,Telekinesis,Kryptonite,0 +Flash,DC Comics,9,10,8,Super Strength,Wooden Stake,1 +Flash,Marvel,9,3,1,Flight,Kryptonite,0 +Flash,DC Comics,4,5,7,Super Strength,Silver,1 +Flash,Marvel,9,5,2,Flight,Magic,0 +Spider-Man,DC Comics,3,4,1,Invisibility,Magic,0 +Superman,Marvel,7,1,3,Super Strength,Silver,1 +Thor,Marvel,6,5,4,Invisibility,Wooden Stake,1 +Spider-Man,DC Comics,8,10,6,Invisibility,Kryptonite,0 +Flash,DC Comics,9,5,10,Super Strength,Silver,1 +Captain America,DC Comics,5,4,5,Flight,Magic,0 +Captain America,DC Comics,1,6,4,Invisibility,Magic,0 +Spider-Man,DC Comics,3,10,8,Invisibility,Silver,0 +Iron Man,Marvel,10,4,4,Super Strength,Magic,0 +Captain America,DC Comics,8,7,10,Super Strength,Silver,1 +Wonder Woman,DC Comics,6,7,2,Super Strength,Magic,0 +Iron Man,DC Comics,8,2,3,Super Strength,Silver,1 +Wonder Woman,DC Comics,9,3,6,Super Strength,Kryptonite,0 +Thor,Marvel,4,1,8,Telekinesis,Kryptonite,0 +Superman,Marvel,1,8,8,Super Strength,Kryptonite,0 +Captain America,Marvel,1,9,9,Flight,Kryptonite,0 +Iron Man,Marvel,10,4,7,Invisibility,Magic,1 +Flash,Marvel,4,6,2,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,7,9,8,Flight,Silver,0 +Spider-Man,Marvel,2,6,7,Telekinesis,Wooden Stake,0 +Wonder Woman,Marvel,3,9,8,Super Strength,Magic,0 +Wonder Woman,DC Comics,1,4,3,Invisibility,Magic,0 +Thor,DC Comics,5,8,7,Flight,Wooden Stake,1 +Batman,Marvel,1,9,10,Super Strength,Wooden Stake,0 +Batman,Marvel,8,4,9,Super Strength,Magic,1 +Spider-Man,DC Comics,1,5,3,Telekinesis,Magic,0 +Thor,Marvel,1,8,10,Telekinesis,Silver,0 +Thor,DC Comics,2,10,6,Telekinesis,Kryptonite,0 +Flash,DC Comics,2,6,2,Invisibility,Kryptonite,0 +Thor,Marvel,6,7,2,Flight,Silver,0 +Thor,Marvel,7,3,5,Telekinesis,Wooden Stake,0 +Batman,Marvel,5,7,5,Telekinesis,Magic,1 +Iron Man,DC Comics,1,8,7,Telekinesis,Wooden Stake,0 +Thor,DC Comics,1,10,2,Flight,Kryptonite,0 +Iron Man,Marvel,3,6,7,Flight,Kryptonite,0 +Wonder Woman,Marvel,2,10,5,Telekinesis,Wooden Stake,0 +Wonder Woman,Marvel,5,9,6,Telekinesis,Kryptonite,0 +Thor,DC Comics,10,6,8,Super Strength,Magic,1 +Captain America,DC Comics,6,9,10,Telekinesis,Silver,1 +Superman,DC Comics,7,4,4,Invisibility,Wooden Stake,0 +Captain America,Marvel,4,8,7,Invisibility,Magic,1 +Wonder Woman,DC Comics,7,4,6,Telekinesis,Magic,0 +Superman,DC Comics,8,2,10,Flight,Kryptonite,1 +Captain America,Marvel,1,10,2,Super Strength,Magic,0 +Thor,DC Comics,6,9,8,Flight,Wooden Stake,1 +Iron Man,Marvel,8,5,10,Telekinesis,Magic,1 +Superman,DC Comics,5,4,9,Invisibility,Silver,0 +Batman,Marvel,4,2,5,Super Strength,Magic,0 +Spider-Man,Marvel,2,1,10,Flight,Magic,0 +Superman,DC Comics,6,7,4,Flight,Silver,0 +Superman,Marvel,6,6,6,Telekinesis,Magic,0 +Batman,DC Comics,1,2,8,Super Strength,Magic,0 +Thor,Marvel,9,8,3,Invisibility,Kryptonite,0 +Captain America,Marvel,6,4,10,Telekinesis,Wooden Stake,0 +Captain America,Marvel,3,8,1,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,4,7,4,Flight,Wooden Stake,1 +Iron Man,Marvel,4,5,4,Telekinesis,Silver,1 +Thor,Marvel,3,10,1,Flight,Silver,0 +Batman,DC Comics,10,10,9,Flight,Silver,1 +Thor,Marvel,3,8,3,Telekinesis,Wooden Stake,0 +Thor,Marvel,3,9,5,Telekinesis,Wooden Stake,0 +Captain America,Marvel,4,5,6,Telekinesis,Wooden Stake,0 +Batman,Marvel,7,10,8,Telekinesis,Silver,1 +Flash,DC Comics,4,5,6,Telekinesis,Wooden Stake,0 +Spider-Man,Marvel,9,2,3,Flight,Magic,0 +Superman,Marvel,1,5,6,Invisibility,Kryptonite,0 +Captain America,DC Comics,8,3,1,Invisibility,Silver,0 +Batman,Marvel,7,7,4,Telekinesis,Kryptonite,0 +Iron Man,Marvel,2,10,6,Flight,Magic,0 +Superman,DC Comics,8,5,7,Invisibility,Wooden Stake,1 +Superman,DC Comics,1,8,10,Invisibility,Kryptonite,0 +Flash,DC Comics,9,1,3,Invisibility,Magic,1 +Flash,DC Comics,9,3,9,Flight,Magic,0 +Captain America,Marvel,2,3,7,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,7,9,1,Telekinesis,Silver,0 +Iron Man,Marvel,10,5,2,Telekinesis,Kryptonite,0 +Captain America,DC Comics,3,9,1,Super Strength,Silver,1 +Thor,Marvel,7,9,9,Super Strength,Wooden Stake,1 +Wonder Woman,DC Comics,10,1,9,Super Strength,Silver,0 +Batman,DC Comics,9,2,7,Flight,Wooden Stake,0 +Flash,Marvel,4,5,10,Invisibility,Kryptonite,0 +Iron Man,DC Comics,1,4,3,Invisibility,Wooden Stake,0 +Superman,DC Comics,2,10,5,Flight,Magic,1 +Captain America,DC Comics,1,9,4,Flight,Wooden Stake,0 +Flash,Marvel,5,7,7,Telekinesis,Silver,1 +Superman,DC Comics,5,6,9,Telekinesis,Silver,1 +Iron Man,DC Comics,7,7,2,Super Strength,Silver,1 +Flash,Marvel,9,1,8,Super Strength,Wooden Stake,0 +Flash,Marvel,9,1,9,Flight,Silver,1 +Superman,DC Comics,3,8,10,Super Strength,Silver,1 +Captain America,Marvel,3,2,10,Invisibility,Magic,0 +Wonder Woman,Marvel,3,10,9,Flight,Wooden Stake,0 +Captain America,Marvel,4,9,10,Flight,Magic,0 +Spider-Man,DC Comics,8,7,7,Invisibility,Silver,1 +Flash,DC Comics,6,6,9,Telekinesis,Silver,1 +Superman,Marvel,8,1,9,Telekinesis,Silver,0 +Spider-Man,DC Comics,1,1,3,Invisibility,Wooden Stake,0 +Wonder Woman,Marvel,8,2,4,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,4,6,2,Super Strength,Silver,1 +Superman,Marvel,1,6,10,Flight,Silver,0 +Iron Man,DC Comics,8,2,3,Super Strength,Silver,1 +Thor,Marvel,4,1,5,Invisibility,Silver,0 +Wonder Woman,DC Comics,6,10,5,Super Strength,Wooden Stake,1 +Captain America,DC Comics,8,5,6,Invisibility,Kryptonite,1 +Batman,Marvel,4,5,7,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,3,2,7,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,9,6,1,Telekinesis,Silver,1 +Iron Man,DC Comics,3,9,2,Invisibility,Silver,0 +Superman,DC Comics,9,2,9,Super Strength,Kryptonite,0 +Iron Man,DC Comics,2,10,10,Flight,Kryptonite,0 +Iron Man,DC Comics,2,2,2,Super Strength,Silver,0 +Superman,DC Comics,2,3,6,Super Strength,Silver,0 +Batman,DC Comics,6,7,1,Flight,Magic,0 +Superman,Marvel,3,6,3,Invisibility,Magic,0 +Batman,DC Comics,9,8,2,Telekinesis,Magic,0 +Superman,Marvel,4,8,3,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,1,6,5,Telekinesis,Wooden Stake,0 +Batman,Marvel,4,10,10,Flight,Silver,0 +Spider-Man,DC Comics,1,3,6,Super Strength,Magic,1 +Wonder Woman,Marvel,5,3,9,Invisibility,Wooden Stake,1 +Batman,Marvel,4,1,10,Super Strength,Silver,1 +Batman,DC Comics,8,7,4,Telekinesis,Wooden Stake,0 +Superman,Marvel,8,5,7,Super Strength,Kryptonite,1 +Batman,DC Comics,7,4,6,Flight,Kryptonite,0 +Spider-Man,DC Comics,3,10,2,Flight,Kryptonite,0 +Flash,Marvel,1,4,10,Invisibility,Magic,0 +Wonder Woman,DC Comics,1,4,8,Invisibility,Silver,0 +Flash,Marvel,3,6,7,Telekinesis,Kryptonite,0 +Superman,Marvel,6,8,7,Invisibility,Magic,1 +Captain America,DC Comics,7,8,8,Super Strength,Magic,1 +Wonder Woman,DC Comics,6,5,1,Flight,Magic,0 +Flash,DC Comics,6,6,1,Flight,Magic,0 +Wonder Woman,DC Comics,6,4,8,Flight,Kryptonite,0 +Flash,DC Comics,3,9,4,Invisibility,Magic,0 +Spider-Man,Marvel,6,8,5,Flight,Kryptonite,0 +Flash,Marvel,8,10,8,Flight,Kryptonite,0 +Wonder Woman,DC Comics,2,10,5,Flight,Magic,1 +Captain America,DC Comics,5,1,10,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,1,2,4,Telekinesis,Silver,0 +Superman,Marvel,1,9,6,Invisibility,Silver,1 +Iron Man,Marvel,5,8,5,Flight,Wooden Stake,0 +Superman,Marvel,3,3,7,Invisibility,Silver,1 +Wonder Woman,DC Comics,4,8,10,Flight,Kryptonite,0 +Superman,DC Comics,3,1,7,Flight,Kryptonite,0 +Flash,Marvel,1,10,4,Flight,Silver,0 +Spider-Man,DC Comics,1,4,5,Invisibility,Magic,0 +Captain America,DC Comics,5,3,3,Invisibility,Magic,0 +Superman,Marvel,6,6,4,Flight,Kryptonite,0 +Captain America,Marvel,3,7,4,Super Strength,Magic,1 +Superman,DC Comics,9,4,3,Invisibility,Wooden Stake,0 +Captain America,Marvel,5,7,10,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,8,9,5,Invisibility,Silver,0 +Spider-Man,Marvel,1,2,5,Flight,Silver,0 +Superman,Marvel,5,3,7,Super Strength,Magic,1 +Thor,DC Comics,3,5,4,Flight,Kryptonite,0 +Captain America,DC Comics,1,3,4,Telekinesis,Silver,0 +Captain America,Marvel,4,8,9,Invisibility,Wooden Stake,1 +Flash,DC Comics,5,10,6,Invisibility,Silver,0 +Thor,Marvel,7,8,4,Flight,Silver,0 +Spider-Man,DC Comics,1,8,2,Flight,Wooden Stake,0 +Captain America,Marvel,3,9,6,Telekinesis,Kryptonite,0 +Spider-Man,Marvel,2,4,2,Super Strength,Silver,0 +Captain America,Marvel,9,5,5,Telekinesis,Silver,0 +Wonder Woman,DC Comics,10,5,6,Super Strength,Silver,1 +Batman,Marvel,6,8,4,Invisibility,Magic,1 +Wonder Woman,Marvel,10,7,3,Super Strength,Silver,1 +Captain America,Marvel,3,9,7,Super Strength,Wooden Stake,0 +Batman,Marvel,8,8,2,Invisibility,Kryptonite,0 +Superman,DC Comics,8,2,6,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,2,10,4,Invisibility,Wooden Stake,1 +Captain America,Marvel,6,4,6,Telekinesis,Magic,0 +Flash,Marvel,7,6,4,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,2,2,4,Flight,Kryptonite,0 +Flash,Marvel,10,7,4,Invisibility,Wooden Stake,1 +Iron Man,DC Comics,2,3,9,Invisibility,Magic,1 +Thor,Marvel,10,3,7,Invisibility,Kryptonite,0 +Iron Man,DC Comics,1,2,3,Super Strength,Magic,0 +Batman,Marvel,8,8,3,Telekinesis,Wooden Stake,1 +Iron Man,DC Comics,1,6,6,Invisibility,Silver,0 +Iron Man,DC Comics,9,1,6,Telekinesis,Wooden Stake,1 +Iron Man,DC Comics,6,1,4,Flight,Magic,0 +Captain America,Marvel,7,7,9,Flight,Wooden Stake,1 +Thor,DC Comics,10,8,4,Invisibility,Silver,1 +Spider-Man,DC Comics,7,5,9,Flight,Magic,1 +Thor,Marvel,10,5,4,Telekinesis,Wooden Stake,0 +Flash,Marvel,3,4,2,Super Strength,Magic,0 +Batman,Marvel,2,6,2,Invisibility,Magic,0 +Captain America,Marvel,9,6,5,Flight,Kryptonite,0 +Superman,DC Comics,8,3,4,Telekinesis,Kryptonite,0 +Captain America,Marvel,10,9,7,Telekinesis,Magic,1 +Wonder Woman,Marvel,7,7,5,Flight,Wooden Stake,0 +Iron Man,Marvel,9,1,6,Telekinesis,Wooden Stake,0 +Flash,Marvel,4,7,10,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,4,5,4,Invisibility,Silver,0 +Batman,Marvel,1,5,2,Telekinesis,Magic,0 +Superman,Marvel,8,2,10,Flight,Magic,0 +Flash,DC Comics,3,4,9,Invisibility,Silver,1 +Wonder Woman,DC Comics,7,6,10,Flight,Magic,0 +Captain America,DC Comics,2,10,7,Super Strength,Magic,1 +Superman,DC Comics,2,7,4,Flight,Silver,0 +Spider-Man,DC Comics,7,5,3,Flight,Kryptonite,0 +Thor,Marvel,6,9,10,Invisibility,Magic,0 +Captain America,Marvel,3,3,3,Telekinesis,Silver,0 +Superman,Marvel,9,1,9,Flight,Wooden Stake,0 +Spider-Man,Marvel,10,4,5,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,6,9,3,Super Strength,Wooden Stake,1 +Wonder Woman,DC Comics,10,4,5,Invisibility,Magic,0 +Wonder Woman,Marvel,10,2,2,Invisibility,Kryptonite,0 +Thor,Marvel,6,10,4,Telekinesis,Silver,0 +Spider-Man,DC Comics,1,5,10,Flight,Magic,0 +Flash,DC Comics,4,3,2,Super Strength,Silver,0 +Batman,DC Comics,10,9,2,Invisibility,Kryptonite,0 +Spider-Man,Marvel,6,4,8,Flight,Wooden Stake,0 +Superman,Marvel,6,6,1,Flight,Magic,0 +Wonder Woman,DC Comics,5,2,7,Invisibility,Magic,0 +Batman,DC Comics,1,6,5,Flight,Silver,0 +Flash,Marvel,8,3,8,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,5,9,1,Invisibility,Silver,0 +Flash,Marvel,5,2,7,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,7,9,5,Super Strength,Magic,1 +Wonder Woman,DC Comics,4,5,4,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,6,8,7,Telekinesis,Magic,0 +Iron Man,DC Comics,4,2,10,Flight,Kryptonite,0 +Spider-Man,Marvel,3,6,2,Super Strength,Wooden Stake,1 +Wonder Woman,Marvel,7,3,1,Flight,Kryptonite,0 +Batman,Marvel,8,10,1,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,4,5,1,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,2,8,5,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,10,10,10,Super Strength,Silver,1 +Spider-Man,Marvel,3,1,7,Super Strength,Silver,0 +Spider-Man,Marvel,1,5,2,Flight,Magic,0 +Batman,DC Comics,8,3,10,Invisibility,Silver,1 +Flash,Marvel,3,4,8,Flight,Kryptonite,0 +Spider-Man,DC Comics,10,2,4,Invisibility,Silver,0 +Thor,DC Comics,7,9,3,Flight,Kryptonite,0 +Superman,DC Comics,10,3,10,Telekinesis,Wooden Stake,1 +Thor,DC Comics,5,2,8,Telekinesis,Kryptonite,0 +Batman,Marvel,10,10,2,Super Strength,Magic,1 +Iron Man,Marvel,5,9,3,Telekinesis,Wooden Stake,0 +Thor,Marvel,7,7,3,Super Strength,Magic,1 +Flash,Marvel,9,6,10,Invisibility,Magic,1 +Wonder Woman,Marvel,5,1,1,Telekinesis,Magic,0 +Superman,Marvel,1,5,6,Invisibility,Silver,0 +Captain America,DC Comics,10,3,2,Flight,Magic,0 +Superman,Marvel,10,1,1,Invisibility,Wooden Stake,0 +Thor,Marvel,1,4,2,Flight,Kryptonite,0 +Captain America,Marvel,2,2,6,Invisibility,Magic,0 +Batman,DC Comics,6,2,4,Invisibility,Wooden Stake,0 +Flash,Marvel,9,3,6,Telekinesis,Magic,0 +Superman,DC Comics,8,8,9,Invisibility,Kryptonite,0 +Iron Man,Marvel,5,8,10,Telekinesis,Wooden Stake,0 +Captain America,Marvel,1,7,10,Telekinesis,Wooden Stake,0 +Captain America,Marvel,7,6,8,Super Strength,Kryptonite,1 +Superman,DC Comics,5,9,1,Super Strength,Wooden Stake,1 +Thor,DC Comics,6,4,8,Flight,Kryptonite,0 +Captain America,Marvel,7,1,9,Invisibility,Wooden Stake,1 +Batman,Marvel,3,8,6,Flight,Wooden Stake,0 +Superman,Marvel,10,7,10,Invisibility,Kryptonite,1 +Batman,DC Comics,3,7,5,Super Strength,Kryptonite,0 +Superman,DC Comics,5,3,6,Super Strength,Wooden Stake,0 +Batman,Marvel,6,4,6,Invisibility,Wooden Stake,1 +Thor,DC Comics,9,10,9,Invisibility,Kryptonite,1 +Superman,DC Comics,5,9,4,Super Strength,Silver,0 +Flash,DC Comics,1,6,2,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,4,5,9,Flight,Wooden Stake,0 +Iron Man,Marvel,5,3,2,Super Strength,Wooden Stake,1 +Thor,Marvel,10,9,10,Invisibility,Wooden Stake,1 +Batman,DC Comics,10,5,9,Flight,Kryptonite,1 +Flash,DC Comics,5,5,2,Invisibility,Wooden Stake,0 +Superman,DC Comics,7,4,8,Telekinesis,Silver,0 +Thor,Marvel,4,4,9,Flight,Magic,0 +Batman,Marvel,1,1,10,Invisibility,Silver,0 +Spider-Man,DC Comics,5,7,9,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,7,9,10,Telekinesis,Wooden Stake,1 +Captain America,DC Comics,10,3,9,Invisibility,Kryptonite,0 +Iron Man,DC Comics,10,2,2,Flight,Magic,0 +Spider-Man,Marvel,6,3,4,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,5,1,7,Telekinesis,Wooden Stake,0 +Batman,Marvel,4,6,2,Flight,Magic,0 +Thor,Marvel,2,7,1,Telekinesis,Magic,0 +Superman,Marvel,4,2,3,Invisibility,Wooden Stake,0 +Thor,Marvel,10,8,4,Super Strength,Wooden Stake,1 +Captain America,DC Comics,10,6,8,Super Strength,Wooden Stake,1 +Flash,DC Comics,3,4,6,Invisibility,Kryptonite,0 +Thor,Marvel,10,5,2,Invisibility,Silver,0 +Spider-Man,Marvel,1,8,9,Invisibility,Kryptonite,0 +Thor,Marvel,8,3,2,Flight,Kryptonite,0 +Spider-Man,DC Comics,5,3,5,Telekinesis,Silver,0 +Spider-Man,DC Comics,4,4,4,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,8,1,7,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,7,9,8,Invisibility,Silver,1 +Wonder Woman,Marvel,2,8,5,Telekinesis,Silver,1 +Wonder Woman,DC Comics,1,8,10,Invisibility,Kryptonite,0 +Batman,Marvel,4,10,5,Flight,Magic,0 +Wonder Woman,DC Comics,8,6,2,Super Strength,Silver,0 +Spider-Man,DC Comics,2,7,8,Invisibility,Kryptonite,0 +Superman,DC Comics,3,6,2,Invisibility,Magic,0 +Captain America,DC Comics,1,9,10,Super Strength,Wooden Stake,1 +Batman,Marvel,1,3,6,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,3,3,8,Flight,Kryptonite,0 +Wonder Woman,Marvel,5,3,6,Telekinesis,Kryptonite,0 +Superman,Marvel,3,10,4,Invisibility,Silver,1 +Thor,Marvel,1,3,4,Telekinesis,Wooden Stake,0 +Captain America,Marvel,1,9,6,Invisibility,Kryptonite,0 +Superman,Marvel,8,4,4,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,10,7,8,Super Strength,Wooden Stake,1 +Captain America,Marvel,2,9,9,Flight,Silver,1 +Captain America,DC Comics,3,7,1,Super Strength,Magic,0 +Wonder Woman,Marvel,2,9,4,Telekinesis,Silver,1 +Thor,DC Comics,3,3,4,Telekinesis,Kryptonite,0 +Thor,Marvel,7,4,2,Flight,Silver,0 +Wonder Woman,DC Comics,1,8,6,Super Strength,Silver,1 +Captain America,Marvel,10,6,3,Flight,Wooden Stake,0 +Superman,Marvel,8,5,7,Super Strength,Silver,1 +Iron Man,Marvel,10,4,5,Super Strength,Kryptonite,0 +Spider-Man,Marvel,10,8,4,Telekinesis,Magic,1 +Thor,DC Comics,10,1,5,Telekinesis,Silver,1 +Wonder Woman,Marvel,2,9,8,Super Strength,Silver,1 +Flash,Marvel,3,1,3,Super Strength,Magic,0 +Iron Man,DC Comics,9,8,7,Super Strength,Kryptonite,1 +Thor,Marvel,7,4,6,Telekinesis,Kryptonite,0 +Flash,DC Comics,4,9,1,Telekinesis,Silver,0 +Captain America,DC Comics,10,5,7,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,5,3,7,Super Strength,Silver,0 +Iron Man,Marvel,2,9,1,Invisibility,Magic,1 +Wonder Woman,DC Comics,8,9,9,Super Strength,Magic,1 +Superman,Marvel,4,4,6,Telekinesis,Magic,0 +Superman,DC Comics,9,4,2,Invisibility,Silver,1 +Batman,Marvel,5,8,5,Invisibility,Silver,0 +Spider-Man,Marvel,9,2,4,Flight,Kryptonite,0 +Spider-Man,DC Comics,4,9,7,Super Strength,Wooden Stake,0 +Thor,Marvel,10,6,8,Telekinesis,Silver,1 +Spider-Man,Marvel,5,9,1,Flight,Kryptonite,0 +Wonder Woman,Marvel,9,8,5,Flight,Silver,1 +Wonder Woman,DC Comics,8,7,3,Super Strength,Kryptonite,0 +Batman,Marvel,3,1,1,Flight,Kryptonite,0 +Flash,DC Comics,1,3,3,Super Strength,Wooden Stake,0 +Superman,Marvel,3,2,6,Flight,Silver,0 +Flash,DC Comics,4,5,7,Super Strength,Kryptonite,0 +Flash,Marvel,2,5,8,Telekinesis,Magic,0 +Iron Man,Marvel,1,5,4,Super Strength,Magic,0 +Iron Man,DC Comics,7,4,3,Super Strength,Magic,1 +Superman,Marvel,8,5,5,Invisibility,Wooden Stake,1 +Captain America,DC Comics,7,3,9,Telekinesis,Kryptonite,0 +Superman,Marvel,5,1,6,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,1,5,9,Telekinesis,Silver,1 +Flash,Marvel,7,9,6,Flight,Silver,1 +Thor,DC Comics,7,9,2,Invisibility,Kryptonite,0 +Batman,Marvel,9,4,5,Telekinesis,Magic,0 +Flash,DC Comics,3,3,9,Flight,Kryptonite,0 +Superman,DC Comics,9,1,8,Flight,Kryptonite,0 +Captain America,Marvel,1,2,7,Flight,Kryptonite,0 +Flash,DC Comics,1,8,1,Invisibility,Wooden Stake,0 +Thor,DC Comics,4,1,4,Flight,Silver,0 +Superman,Marvel,9,8,7,Invisibility,Kryptonite,0 +Thor,Marvel,6,7,7,Super Strength,Kryptonite,0 +Flash,Marvel,3,8,6,Flight,Kryptonite,0 +Superman,Marvel,1,6,8,Telekinesis,Wooden Stake,0 +Thor,Marvel,4,9,6,Flight,Wooden Stake,0 +Wonder Woman,Marvel,9,3,10,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,3,10,3,Super Strength,Kryptonite,0 +Thor,DC Comics,9,4,4,Flight,Magic,0 +Wonder Woman,DC Comics,7,6,3,Super Strength,Magic,1 +Flash,Marvel,4,8,1,Invisibility,Magic,0 +Spider-Man,Marvel,3,5,10,Invisibility,Silver,1 +Iron Man,DC Comics,10,3,5,Flight,Kryptonite,0 +Spider-Man,DC Comics,5,6,1,Invisibility,Magic,0 +Thor,Marvel,5,4,1,Invisibility,Magic,0 +Batman,DC Comics,3,9,2,Telekinesis,Magic,0 +Batman,Marvel,9,3,4,Flight,Kryptonite,0 +Iron Man,Marvel,4,4,6,Super Strength,Magic,1 +Thor,DC Comics,5,7,8,Flight,Magic,0 +Spider-Man,Marvel,4,7,3,Invisibility,Kryptonite,0 +Batman,Marvel,5,4,1,Telekinesis,Silver,0 +Superman,Marvel,7,6,3,Flight,Wooden Stake,1 +Captain America,Marvel,9,3,3,Flight,Magic,0 +Thor,DC Comics,7,6,5,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,5,2,4,Invisibility,Silver,0 +Wonder Woman,Marvel,10,8,4,Flight,Silver,1 +Superman,DC Comics,10,2,9,Invisibility,Magic,0 +Superman,Marvel,7,7,7,Invisibility,Kryptonite,1 +Thor,Marvel,10,9,4,Invisibility,Silver,1 +Captain America,DC Comics,5,1,3,Invisibility,Wooden Stake,1 +Batman,DC Comics,3,8,6,Invisibility,Wooden Stake,0 +Captain America,Marvel,7,7,3,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,2,6,6,Invisibility,Wooden Stake,0 +Spider-Man,DC Comics,9,6,9,Super Strength,Silver,1 +Spider-Man,Marvel,10,6,6,Flight,Magic,0 +Superman,Marvel,10,9,4,Telekinesis,Magic,0 +Batman,Marvel,1,2,5,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,6,1,6,Invisibility,Magic,0 +Superman,Marvel,7,6,3,Flight,Wooden Stake,0 +Thor,DC Comics,8,10,8,Super Strength,Wooden Stake,1 +Superman,DC Comics,10,8,4,Invisibility,Kryptonite,0 +Thor,DC Comics,9,3,8,Flight,Silver,1 +Thor,DC Comics,2,10,10,Invisibility,Silver,0 +Iron Man,Marvel,10,1,10,Invisibility,Wooden Stake,1 +Iron Man,DC Comics,2,9,3,Invisibility,Silver,0 +Thor,Marvel,5,1,10,Invisibility,Magic,1 +Flash,DC Comics,5,3,7,Invisibility,Wooden Stake,0 +Batman,DC Comics,6,8,9,Invisibility,Kryptonite,0 +Iron Man,Marvel,3,3,4,Invisibility,Magic,1 +Iron Man,DC Comics,8,4,8,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,1,8,3,Telekinesis,Kryptonite,0 +Superman,Marvel,6,1,7,Super Strength,Silver,0 +Spider-Man,DC Comics,4,6,3,Invisibility,Silver,0 +Batman,DC Comics,1,1,7,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,7,1,10,Super Strength,Silver,1 +Wonder Woman,Marvel,9,8,10,Super Strength,Kryptonite,1 +Flash,DC Comics,4,4,6,Telekinesis,Kryptonite,0 +Iron Man,Marvel,4,1,2,Super Strength,Magic,0 +Captain America,Marvel,6,10,3,Telekinesis,Kryptonite,0 +Batman,Marvel,3,7,6,Invisibility,Wooden Stake,1 +Wonder Woman,DC Comics,6,5,4,Flight,Wooden Stake,0 +Superman,DC Comics,7,5,6,Flight,Silver,0 +Superman,DC Comics,10,1,1,Flight,Silver,0 +Wonder Woman,DC Comics,10,10,10,Flight,Silver,1 +Superman,Marvel,3,6,1,Invisibility,Wooden Stake,0 +Flash,Marvel,7,9,3,Flight,Kryptonite,0 +Wonder Woman,DC Comics,3,9,8,Super Strength,Silver,0 +Batman,DC Comics,2,8,8,Super Strength,Magic,1 +Wonder Woman,Marvel,10,5,4,Flight,Silver,0 +Wonder Woman,DC Comics,4,1,6,Super Strength,Wooden Stake,0 +Captain America,DC Comics,8,9,8,Telekinesis,Silver,1 +Captain America,DC Comics,9,1,7,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,7,8,7,Flight,Silver,1 +Batman,DC Comics,1,5,4,Flight,Wooden Stake,0 +Batman,DC Comics,3,3,9,Invisibility,Wooden Stake,1 +Captain America,Marvel,9,7,10,Super Strength,Magic,1 +Thor,Marvel,1,7,6,Invisibility,Wooden Stake,0 +Thor,Marvel,9,9,3,Invisibility,Magic,1 +Spider-Man,Marvel,8,7,5,Super Strength,Kryptonite,0 +Flash,DC Comics,1,3,5,Invisibility,Wooden Stake,0 +Thor,DC Comics,6,1,5,Super Strength,Silver,0 +Thor,Marvel,5,8,8,Super Strength,Kryptonite,0 +Thor,Marvel,6,3,9,Invisibility,Silver,0 +Flash,Marvel,10,8,9,Telekinesis,Silver,1 +Iron Man,Marvel,5,8,6,Super Strength,Silver,0 +Spider-Man,Marvel,6,5,6,Invisibility,Kryptonite,0 +Captain America,DC Comics,5,1,9,Super Strength,Kryptonite,0 +Thor,DC Comics,5,10,4,Telekinesis,Wooden Stake,0 +Superman,Marvel,4,7,6,Telekinesis,Silver,0 +Wonder Woman,Marvel,3,10,4,Flight,Magic,0 +Iron Man,DC Comics,3,5,1,Super Strength,Wooden Stake,0 +Flash,DC Comics,4,8,7,Super Strength,Kryptonite,0 +Flash,DC Comics,9,9,10,Invisibility,Magic,1 +Flash,Marvel,2,7,6,Super Strength,Kryptonite,0 +Thor,DC Comics,9,7,9,Flight,Magic,1 +Wonder Woman,Marvel,1,1,7,Telekinesis,Wooden Stake,0 +Wonder Woman,Marvel,1,4,7,Telekinesis,Magic,0 +Iron Man,DC Comics,5,2,2,Flight,Wooden Stake,0 +Spider-Man,DC Comics,6,2,9,Super Strength,Kryptonite,1 +Flash,DC Comics,6,2,10,Super Strength,Magic,0 +Superman,Marvel,3,4,9,Flight,Silver,1 +Superman,DC Comics,7,1,6,Invisibility,Silver,1 +Superman,DC Comics,9,4,3,Telekinesis,Kryptonite,0 +Flash,Marvel,10,2,1,Flight,Magic,0 +Thor,DC Comics,8,5,4,Flight,Silver,0 +Iron Man,DC Comics,6,3,3,Super Strength,Wooden Stake,0 +Flash,Marvel,8,8,1,Telekinesis,Magic,1 +Superman,Marvel,5,4,3,Super Strength,Magic,0 +Wonder Woman,Marvel,8,1,4,Flight,Silver,0 +Flash,Marvel,10,1,8,Invisibility,Wooden Stake,0 +Wonder Woman,Marvel,4,10,9,Telekinesis,Wooden Stake,0 +Batman,DC Comics,10,3,3,Flight,Wooden Stake,0 +Flash,DC Comics,8,9,6,Flight,Magic,0 +Batman,Marvel,10,7,10,Invisibility,Kryptonite,0 +Iron Man,DC Comics,2,2,5,Flight,Magic,0 +Flash,DC Comics,5,9,6,Flight,Magic,0 +Thor,Marvel,9,10,4,Telekinesis,Silver,0 +Thor,Marvel,4,2,10,Telekinesis,Kryptonite,0 +Spider-Man,Marvel,6,3,6,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,1,10,7,Super Strength,Silver,0 +Superman,Marvel,9,2,9,Invisibility,Magic,1 +Captain America,DC Comics,1,3,10,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,5,6,7,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,4,9,6,Super Strength,Wooden Stake,1 +Thor,DC Comics,3,9,1,Invisibility,Magic,0 +Wonder Woman,Marvel,6,7,2,Invisibility,Wooden Stake,0 +Captain America,DC Comics,2,3,1,Flight,Wooden Stake,0 +Spider-Man,Marvel,3,4,9,Super Strength,Kryptonite,0 +Iron Man,DC Comics,5,6,10,Telekinesis,Silver,1 +Batman,Marvel,9,5,10,Invisibility,Kryptonite,0 +Spider-Man,Marvel,2,2,9,Super Strength,Silver,1 +Flash,Marvel,10,6,7,Telekinesis,Silver,0 +Spider-Man,DC Comics,8,3,2,Super Strength,Silver,0 +Flash,DC Comics,2,8,6,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,5,2,4,Flight,Kryptonite,0 +Thor,Marvel,7,1,1,Super Strength,Wooden Stake,0 +Superman,DC Comics,8,9,1,Telekinesis,Magic,1 +Iron Man,DC Comics,1,3,5,Invisibility,Kryptonite,0 +Superman,DC Comics,6,1,2,Flight,Silver,0 +Spider-Man,Marvel,1,7,4,Telekinesis,Wooden Stake,0 +Thor,DC Comics,2,10,1,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,1,5,4,Telekinesis,Kryptonite,0 +Spider-Man,Marvel,5,5,6,Super Strength,Kryptonite,0 +Iron Man,Marvel,10,1,10,Invisibility,Silver,0 +Captain America,Marvel,9,9,4,Telekinesis,Silver,1 +Batman,Marvel,6,7,1,Super Strength,Magic,0 +Captain America,Marvel,1,8,7,Invisibility,Silver,0 +Iron Man,Marvel,1,9,2,Invisibility,Wooden Stake,1 +Wonder Woman,DC Comics,2,6,9,Super Strength,Magic,0 +Captain America,DC Comics,9,5,3,Super Strength,Magic,1 +Iron Man,Marvel,3,6,8,Telekinesis,Magic,0 +Wonder Woman,DC Comics,1,2,8,Invisibility,Kryptonite,0 +Spider-Man,Marvel,5,4,3,Flight,Silver,0 +Wonder Woman,DC Comics,7,3,4,Super Strength,Magic,0 +Thor,Marvel,6,7,2,Invisibility,Kryptonite,0 +Batman,Marvel,1,9,4,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,5,5,9,Telekinesis,Magic,0 +Thor,DC Comics,5,6,2,Flight,Magic,0 +Thor,DC Comics,6,10,3,Telekinesis,Wooden Stake,0 +Thor,DC Comics,3,2,4,Flight,Magic,0 +Wonder Woman,DC Comics,5,3,5,Flight,Wooden Stake,0 +Iron Man,DC Comics,7,3,1,Super Strength,Magic,0 +Flash,DC Comics,5,9,7,Invisibility,Magic,1 +Iron Man,DC Comics,5,7,10,Invisibility,Silver,0 +Batman,Marvel,5,8,7,Invisibility,Magic,1 +Iron Man,DC Comics,10,10,9,Flight,Magic,1 +Superman,DC Comics,10,9,4,Invisibility,Wooden Stake,1 +Iron Man,Marvel,3,6,6,Super Strength,Wooden Stake,0 +Iron Man,Marvel,1,4,2,Flight,Silver,0 +Iron Man,Marvel,5,1,4,Flight,Magic,0 +Spider-Man,Marvel,9,8,2,Flight,Magic,1 +Batman,DC Comics,1,7,10,Flight,Wooden Stake,0 +Superman,DC Comics,3,2,5,Super Strength,Kryptonite,0 +Iron Man,Marvel,4,8,7,Invisibility,Kryptonite,0 +Flash,Marvel,1,5,1,Super Strength,Kryptonite,0 +Batman,DC Comics,1,7,10,Invisibility,Wooden Stake,1 +Captain America,DC Comics,8,4,10,Super Strength,Wooden Stake,1 +Spider-Man,DC Comics,2,5,7,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,8,8,10,Telekinesis,Kryptonite,0 +Flash,Marvel,7,1,6,Telekinesis,Magic,0 +Iron Man,DC Comics,10,1,6,Telekinesis,Wooden Stake,1 +Flash,Marvel,10,4,8,Flight,Wooden Stake,1 +Superman,Marvel,2,3,8,Flight,Kryptonite,0 +Spider-Man,Marvel,6,10,6,Super Strength,Kryptonite,0 +Superman,DC Comics,6,2,3,Super Strength,Silver,0 +Wonder Woman,Marvel,3,3,5,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,2,1,2,Invisibility,Silver,0 +Flash,Marvel,1,1,5,Telekinesis,Magic,0 +Spider-Man,DC Comics,6,6,9,Super Strength,Silver,1 +Captain America,Marvel,5,5,10,Telekinesis,Kryptonite,0 +Flash,Marvel,9,8,1,Super Strength,Wooden Stake,1 +Batman,DC Comics,1,2,10,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,7,4,5,Invisibility,Silver,0 +Thor,Marvel,5,8,6,Telekinesis,Silver,0 +Wonder Woman,Marvel,5,6,7,Invisibility,Magic,1 +Captain America,DC Comics,2,1,9,Invisibility,Magic,0 +Flash,Marvel,3,4,6,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,7,1,5,Invisibility,Kryptonite,0 +Thor,DC Comics,6,2,7,Flight,Kryptonite,0 +Captain America,Marvel,2,5,1,Flight,Silver,0 +Wonder Woman,DC Comics,6,8,5,Flight,Silver,0 +Thor,Marvel,2,8,2,Super Strength,Wooden Stake,0 +Thor,DC Comics,2,3,4,Flight,Kryptonite,0 +Wonder Woman,DC Comics,2,4,7,Super Strength,Silver,1 +Flash,Marvel,3,10,5,Super Strength,Wooden Stake,0 +Wonder Woman,DC Comics,2,6,6,Flight,Kryptonite,0 +Superman,Marvel,4,10,2,Invisibility,Magic,0 +Spider-Man,DC Comics,9,3,3,Telekinesis,Magic,0 +Spider-Man,DC Comics,6,2,7,Super Strength,Silver,0 +Captain America,DC Comics,1,6,2,Flight,Wooden Stake,0 +Batman,DC Comics,8,5,6,Super Strength,Magic,1 +Wonder Woman,Marvel,7,10,5,Invisibility,Wooden Stake,1 +Flash,DC Comics,10,5,10,Invisibility,Wooden Stake,1 +Superman,DC Comics,3,10,1,Flight,Magic,0 +Spider-Man,DC Comics,1,5,10,Super Strength,Wooden Stake,0 +Spider-Man,Marvel,5,10,4,Telekinesis,Magic,1 +Flash,Marvel,4,5,2,Telekinesis,Silver,0 +Superman,Marvel,10,3,4,Super Strength,Kryptonite,0 +Iron Man,Marvel,8,7,1,Super Strength,Kryptonite,0 +Superman,DC Comics,1,6,2,Super Strength,Silver,0 +Flash,DC Comics,10,4,8,Flight,Magic,0 +Spider-Man,DC Comics,1,2,6,Invisibility,Magic,0 +Batman,Marvel,4,9,2,Telekinesis,Magic,0 +Iron Man,Marvel,8,1,6,Flight,Magic,0 +Flash,DC Comics,5,4,10,Super Strength,Silver,0 +Flash,DC Comics,2,1,9,Super Strength,Kryptonite,0 +Thor,DC Comics,6,6,7,Invisibility,Wooden Stake,1 +Superman,Marvel,5,4,9,Super Strength,Wooden Stake,1 +Thor,DC Comics,2,5,5,Flight,Kryptonite,0 +Iron Man,DC Comics,3,5,7,Flight,Silver,0 +Iron Man,Marvel,9,9,7,Invisibility,Wooden Stake,1 +Iron Man,Marvel,7,1,3,Flight,Kryptonite,0 +Captain America,DC Comics,7,2,7,Telekinesis,Silver,0 +Superman,Marvel,6,6,1,Flight,Wooden Stake,0 +Flash,DC Comics,8,5,9,Flight,Magic,1 +Wonder Woman,DC Comics,4,7,10,Flight,Magic,0 +Batman,DC Comics,8,3,6,Telekinesis,Silver,0 +Batman,DC Comics,4,3,5,Super Strength,Magic,0 +Flash,Marvel,8,10,7,Flight,Silver,0 +Thor,Marvel,9,2,5,Invisibility,Kryptonite,0 +Flash,Marvel,3,3,10,Telekinesis,Kryptonite,0 +Thor,DC Comics,3,10,5,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,2,1,10,Flight,Silver,0 +Thor,DC Comics,10,5,7,Invisibility,Wooden Stake,1 +Superman,Marvel,3,5,10,Flight,Wooden Stake,0 +Spider-Man,Marvel,3,7,7,Telekinesis,Kryptonite,0 +Thor,DC Comics,5,4,3,Invisibility,Wooden Stake,0 +Iron Man,Marvel,5,3,3,Invisibility,Magic,0 +Thor,Marvel,2,1,10,Flight,Wooden Stake,0 +Iron Man,Marvel,10,8,3,Flight,Silver,1 +Captain America,Marvel,6,3,6,Super Strength,Magic,1 +Spider-Man,DC Comics,5,2,6,Flight,Kryptonite,0 +Spider-Man,Marvel,6,4,3,Flight,Silver,0 +Wonder Woman,DC Comics,1,3,3,Super Strength,Magic,0 +Superman,Marvel,5,1,8,Flight,Silver,0 +Flash,DC Comics,9,3,8,Flight,Magic,1 +Superman,DC Comics,10,2,7,Super Strength,Silver,1 +Batman,Marvel,2,8,10,Telekinesis,Silver,0 +Captain America,DC Comics,1,6,4,Telekinesis,Magic,0 +Wonder Woman,DC Comics,10,9,4,Flight,Kryptonite,0 +Superman,Marvel,9,8,3,Flight,Kryptonite,0 +Iron Man,DC Comics,10,10,5,Super Strength,Silver,1 +Captain America,Marvel,9,3,3,Super Strength,Silver,0 +Spider-Man,DC Comics,9,5,8,Telekinesis,Kryptonite,0 +Flash,Marvel,6,7,7,Invisibility,Kryptonite,0 +Flash,Marvel,8,5,3,Flight,Wooden Stake,0 +Iron Man,Marvel,1,8,9,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,10,5,5,Invisibility,Silver,1 +Wonder Woman,Marvel,4,1,9,Super Strength,Magic,0 +Captain America,DC Comics,1,5,7,Flight,Kryptonite,0 +Spider-Man,DC Comics,8,4,7,Flight,Wooden Stake,1 +Superman,Marvel,1,6,6,Super Strength,Wooden Stake,1 +Iron Man,DC Comics,3,3,2,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,4,5,9,Super Strength,Magic,0 +Spider-Man,DC Comics,8,2,6,Telekinesis,Kryptonite,0 +Iron Man,Marvel,6,6,8,Flight,Kryptonite,0 +Flash,Marvel,10,6,1,Telekinesis,Kryptonite,0 +Superman,DC Comics,7,5,5,Super Strength,Magic,0 +Superman,Marvel,8,6,1,Flight,Magic,0 +Superman,Marvel,2,7,10,Telekinesis,Silver,1 +Spider-Man,DC Comics,10,5,8,Telekinesis,Wooden Stake,1 +Thor,Marvel,8,1,8,Invisibility,Wooden Stake,1 +Thor,Marvel,3,8,1,Flight,Kryptonite,0 +Wonder Woman,Marvel,7,4,9,Telekinesis,Magic,1 +Wonder Woman,Marvel,3,9,2,Telekinesis,Magic,0 +Flash,Marvel,7,10,9,Invisibility,Kryptonite,0 +Iron Man,DC Comics,2,6,1,Telekinesis,Kryptonite,0 +Superman,Marvel,10,1,10,Telekinesis,Silver,1 +Iron Man,Marvel,6,3,9,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,3,3,4,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,3,10,9,Telekinesis,Wooden Stake,1 +Batman,Marvel,9,4,7,Telekinesis,Silver,1 +Thor,DC Comics,7,6,6,Flight,Kryptonite,0 +Iron Man,Marvel,5,7,5,Flight,Kryptonite,0 +Iron Man,DC Comics,10,10,9,Invisibility,Wooden Stake,1 +Captain America,Marvel,7,4,2,Super Strength,Wooden Stake,0 +Flash,DC Comics,9,6,2,Flight,Silver,0 +Iron Man,Marvel,1,1,9,Invisibility,Magic,0 +Batman,DC Comics,7,8,3,Telekinesis,Magic,1 +Thor,Marvel,6,7,8,Telekinesis,Wooden Stake,0 +Captain America,Marvel,10,9,9,Invisibility,Silver,1 +Flash,Marvel,9,3,8,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,1,2,4,Telekinesis,Magic,0 +Wonder Woman,DC Comics,4,1,1,Super Strength,Wooden Stake,0 +Spider-Man,Marvel,9,3,4,Telekinesis,Magic,0 +Thor,Marvel,4,5,9,Flight,Magic,0 +Wonder Woman,Marvel,10,2,2,Telekinesis,Magic,0 +Spider-Man,Marvel,3,3,3,Invisibility,Kryptonite,0 +Flash,DC Comics,9,4,10,Super Strength,Kryptonite,1 +Batman,DC Comics,2,7,8,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,4,3,6,Invisibility,Magic,0 +Thor,Marvel,6,9,8,Flight,Kryptonite,1 +Wonder Woman,Marvel,2,8,7,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,8,4,5,Super Strength,Wooden Stake,0 +Iron Man,DC Comics,8,1,9,Telekinesis,Wooden Stake,1 +Spider-Man,DC Comics,1,1,4,Invisibility,Wooden Stake,0 +Spider-Man,DC Comics,3,1,6,Super Strength,Wooden Stake,0 +Captain America,Marvel,10,1,2,Telekinesis,Silver,0 +Batman,Marvel,9,8,2,Flight,Magic,0 +Flash,Marvel,5,3,2,Super Strength,Wooden Stake,1 +Flash,DC Comics,6,6,10,Flight,Silver,0 +Captain America,Marvel,4,3,7,Invisibility,Magic,1 +Thor,DC Comics,10,5,2,Telekinesis,Kryptonite,0 +Captain America,DC Comics,2,7,2,Flight,Wooden Stake,0 +Spider-Man,DC Comics,8,2,9,Invisibility,Silver,1 +Batman,DC Comics,6,6,7,Telekinesis,Kryptonite,0 +Batman,DC Comics,5,6,3,Invisibility,Silver,0 +Superman,Marvel,9,3,3,Flight,Magic,0 +Captain America,Marvel,1,6,7,Invisibility,Magic,0 +Thor,Marvel,5,10,5,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,6,10,10,Telekinesis,Silver,0 +Iron Man,Marvel,5,5,6,Invisibility,Wooden Stake,1 +Flash,DC Comics,6,2,8,Flight,Wooden Stake,1 +Flash,Marvel,6,9,9,Telekinesis,Kryptonite,0 +Flash,DC Comics,7,8,1,Super Strength,Kryptonite,0 +Batman,DC Comics,4,3,3,Telekinesis,Kryptonite,0 +Flash,Marvel,8,8,7,Super Strength,Silver,1 +Captain America,DC Comics,7,9,6,Telekinesis,Wooden Stake,0 +Superman,Marvel,9,3,7,Invisibility,Wooden Stake,0 +Thor,Marvel,7,3,8,Invisibility,Wooden Stake,0 +Thor,Marvel,3,2,6,Flight,Kryptonite,0 +Wonder Woman,DC Comics,3,8,3,Super Strength,Wooden Stake,0 +Flash,DC Comics,8,10,2,Flight,Magic,1 +Spider-Man,DC Comics,5,1,7,Invisibility,Kryptonite,0 +Batman,DC Comics,4,8,1,Super Strength,Wooden Stake,0 +Spider-Man,Marvel,8,7,3,Flight,Silver,1 +Flash,DC Comics,6,7,4,Flight,Kryptonite,0 +Superman,Marvel,2,3,1,Flight,Magic,0 +Iron Man,Marvel,4,1,5,Flight,Magic,0 +Flash,DC Comics,4,4,10,Flight,Silver,0 +Iron Man,DC Comics,6,9,3,Super Strength,Silver,1 +Iron Man,Marvel,6,5,2,Flight,Kryptonite,0 +Thor,DC Comics,1,1,3,Super Strength,Kryptonite,0 +Batman,Marvel,8,5,8,Flight,Magic,1 +Flash,DC Comics,6,8,6,Invisibility,Silver,1 +Spider-Man,DC Comics,3,8,7,Invisibility,Kryptonite,0 +Spider-Man,Marvel,9,5,6,Flight,Magic,0 +Superman,Marvel,2,9,6,Telekinesis,Silver,0 +Iron Man,Marvel,8,1,3,Invisibility,Magic,1 +Batman,DC Comics,10,4,8,Super Strength,Wooden Stake,1 +Batman,DC Comics,3,3,7,Flight,Silver,0 +Superman,DC Comics,5,2,7,Super Strength,Kryptonite,0 +Captain America,Marvel,6,8,6,Telekinesis,Kryptonite,0 +Batman,Marvel,10,7,5,Flight,Wooden Stake,0 +Batman,DC Comics,6,9,10,Invisibility,Silver,0 +Spider-Man,Marvel,4,2,8,Super Strength,Magic,1 +Superman,DC Comics,3,4,5,Invisibility,Kryptonite,0 +Flash,Marvel,4,6,9,Invisibility,Wooden Stake,1 +Batman,DC Comics,1,3,9,Flight,Wooden Stake,0 +Batman,DC Comics,4,8,1,Super Strength,Silver,0 +Spider-Man,DC Comics,1,3,6,Telekinesis,Silver,0 +Flash,Marvel,1,2,7,Invisibility,Kryptonite,0 +Flash,Marvel,10,3,3,Flight,Wooden Stake,1 +Batman,DC Comics,6,6,7,Flight,Magic,0 +Spider-Man,DC Comics,5,2,7,Telekinesis,Wooden Stake,0 +Captain America,DC Comics,4,8,2,Flight,Magic,1 +Thor,DC Comics,3,1,7,Invisibility,Magic,0 +Wonder Woman,DC Comics,1,7,1,Flight,Kryptonite,0 +Spider-Man,DC Comics,6,2,5,Super Strength,Wooden Stake,1 +Spider-Man,Marvel,2,10,9,Super Strength,Magic,1 +Batman,Marvel,8,6,7,Invisibility,Silver,1 +Spider-Man,Marvel,10,2,7,Super Strength,Magic,1 +Superman,Marvel,5,2,2,Telekinesis,Silver,0 +Iron Man,DC Comics,7,10,8,Flight,Silver,1 +Iron Man,DC Comics,10,8,3,Invisibility,Wooden Stake,0 +Captain America,DC Comics,2,2,8,Telekinesis,Silver,0 +Flash,Marvel,8,7,3,Flight,Magic,0 +Spider-Man,Marvel,2,3,10,Telekinesis,Silver,1 +Flash,DC Comics,4,8,7,Invisibility,Wooden Stake,0 +Superman,Marvel,1,7,2,Invisibility,Kryptonite,0 +Batman,Marvel,5,8,4,Telekinesis,Magic,0 +Batman,DC Comics,9,7,6,Flight,Magic,0 +Wonder Woman,DC Comics,1,6,9,Super Strength,Wooden Stake,1 +Thor,DC Comics,9,7,5,Super Strength,Wooden Stake,0 +Captain America,Marvel,8,5,9,Telekinesis,Wooden Stake,1 +Superman,DC Comics,6,7,5,Invisibility,Wooden Stake,0 +Flash,DC Comics,7,1,10,Flight,Magic,1 +Superman,DC Comics,3,1,8,Flight,Kryptonite,0 +Wonder Woman,Marvel,1,9,1,Invisibility,Silver,0 +Wonder Woman,Marvel,5,5,7,Super Strength,Silver,1 +Batman,DC Comics,2,5,4,Flight,Kryptonite,0 +Flash,DC Comics,5,3,5,Telekinesis,Kryptonite,0 +Thor,Marvel,8,5,6,Super Strength,Kryptonite,1 +Batman,Marvel,9,3,5,Telekinesis,Wooden Stake,0 +Thor,DC Comics,2,9,1,Super Strength,Magic,0 +Iron Man,Marvel,3,9,9,Invisibility,Magic,1 +Superman,DC Comics,3,6,2,Telekinesis,Magic,0 +Wonder Woman,DC Comics,1,1,9,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,8,7,10,Invisibility,Magic,1 +Flash,DC Comics,6,7,2,Telekinesis,Wooden Stake,0 +Batman,DC Comics,8,10,9,Super Strength,Magic,1 +Captain America,Marvel,9,10,6,Flight,Kryptonite,0 +Spider-Man,DC Comics,5,4,9,Flight,Silver,1 +Captain America,Marvel,3,8,6,Invisibility,Silver,1 +Captain America,DC Comics,5,6,6,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,5,4,2,Telekinesis,Magic,0 +Superman,Marvel,5,4,8,Telekinesis,Silver,0 +Iron Man,Marvel,3,2,3,Flight,Kryptonite,0 +Iron Man,Marvel,10,2,7,Telekinesis,Kryptonite,0 +Superman,Marvel,4,4,5,Flight,Kryptonite,0 +Spider-Man,Marvel,9,5,3,Invisibility,Wooden Stake,0 +Thor,Marvel,10,8,1,Telekinesis,Wooden Stake,1 +Captain America,DC Comics,9,6,8,Super Strength,Magic,0 +Batman,Marvel,2,4,3,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,8,7,2,Flight,Magic,0 +Superman,Marvel,8,8,1,Invisibility,Magic,0 +Batman,DC Comics,7,2,4,Flight,Kryptonite,0 +Wonder Woman,DC Comics,8,7,8,Telekinesis,Magic,0 +Spider-Man,Marvel,3,2,3,Flight,Silver,0 +Batman,DC Comics,6,2,1,Flight,Wooden Stake,0 +Flash,DC Comics,1,8,4,Invisibility,Magic,0 +Batman,DC Comics,7,2,9,Super Strength,Kryptonite,0 +Flash,Marvel,1,9,1,Telekinesis,Wooden Stake,0 +Captain America,Marvel,9,1,2,Invisibility,Wooden Stake,0 +Spider-Man,DC Comics,1,9,9,Super Strength,Magic,0 +Batman,Marvel,1,1,2,Flight,Silver,0 +Iron Man,Marvel,7,10,3,Super Strength,Magic,1 +Spider-Man,DC Comics,2,10,7,Flight,Silver,1 +Iron Man,DC Comics,5,2,3,Flight,Wooden Stake,0 +Superman,Marvel,8,6,9,Invisibility,Magic,1 +Superman,Marvel,8,6,6,Flight,Kryptonite,0 +Wonder Woman,Marvel,3,1,3,Invisibility,Magic,0 +Thor,DC Comics,7,7,9,Super Strength,Silver,1 +Superman,Marvel,3,8,1,Super Strength,Silver,0 +Batman,Marvel,6,2,10,Flight,Magic,1 +Spider-Man,Marvel,6,8,3,Invisibility,Silver,0 +Superman,DC Comics,3,9,1,Flight,Wooden Stake,0 +Iron Man,DC Comics,7,6,2,Invisibility,Magic,1 +Batman,DC Comics,3,5,8,Invisibility,Silver,0 +Superman,Marvel,8,9,7,Invisibility,Magic,1 +Flash,Marvel,10,9,2,Super Strength,Magic,1 +Flash,DC Comics,4,1,2,Invisibility,Kryptonite,0 +Captain America,Marvel,1,3,9,Super Strength,Magic,0 +Iron Man,Marvel,4,9,6,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,7,2,5,Super Strength,Silver,1 +Wonder Woman,DC Comics,4,4,10,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,6,4,6,Super Strength,Kryptonite,0 +Iron Man,Marvel,9,2,9,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,1,3,7,Flight,Wooden Stake,0 +Thor,Marvel,5,3,10,Invisibility,Kryptonite,1 +Captain America,DC Comics,7,1,10,Telekinesis,Magic,0 +Thor,Marvel,1,6,9,Flight,Kryptonite,0 +Flash,DC Comics,4,8,4,Invisibility,Magic,1 +Superman,DC Comics,6,3,2,Telekinesis,Kryptonite,0 +Captain America,Marvel,2,5,8,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,10,1,4,Telekinesis,Silver,0 +Thor,DC Comics,5,10,9,Invisibility,Kryptonite,0 +Batman,Marvel,10,7,4,Telekinesis,Kryptonite,0 +Captain America,DC Comics,1,10,8,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,6,1,9,Flight,Kryptonite,0 +Spider-Man,Marvel,6,9,9,Super Strength,Magic,0 +Captain America,Marvel,4,8,10,Invisibility,Kryptonite,1 +Captain America,Marvel,8,7,4,Super Strength,Kryptonite,0 +Superman,DC Comics,4,10,1,Flight,Silver,0 +Batman,DC Comics,8,7,3,Super Strength,Silver,0 +Superman,Marvel,8,5,9,Telekinesis,Kryptonite,1 +Wonder Woman,Marvel,5,5,4,Telekinesis,Wooden Stake,0 +Captain America,Marvel,4,5,5,Invisibility,Silver,0 +Flash,Marvel,2,1,7,Invisibility,Kryptonite,0 +Captain America,Marvel,3,8,5,Invisibility,Silver,0 +Wonder Woman,DC Comics,3,1,4,Flight,Kryptonite,0 +Batman,DC Comics,4,4,2,Invisibility,Silver,0 +Batman,Marvel,4,9,2,Flight,Silver,0 +Flash,DC Comics,10,9,4,Telekinesis,Magic,1 +Flash,DC Comics,5,5,10,Super Strength,Kryptonite,0 +Thor,Marvel,4,4,10,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,10,3,9,Telekinesis,Kryptonite,1 +Iron Man,DC Comics,8,3,8,Telekinesis,Kryptonite,0 +Thor,DC Comics,6,5,3,Invisibility,Silver,0 +Iron Man,DC Comics,6,10,9,Invisibility,Magic,1 +Captain America,Marvel,8,1,5,Invisibility,Magic,0 +Thor,DC Comics,7,5,3,Super Strength,Wooden Stake,0 +Thor,DC Comics,10,6,5,Invisibility,Kryptonite,1 +Iron Man,DC Comics,10,7,10,Flight,Wooden Stake,1 +Spider-Man,Marvel,8,9,4,Telekinesis,Silver,0 +Flash,DC Comics,2,3,8,Super Strength,Wooden Stake,1 +Iron Man,DC Comics,9,2,5,Super Strength,Kryptonite,1 +Superman,DC Comics,1,3,10,Super Strength,Magic,0 +Spider-Man,Marvel,8,9,8,Super Strength,Magic,1 +Thor,Marvel,4,7,9,Super Strength,Kryptonite,0 +Spider-Man,Marvel,4,9,4,Flight,Silver,0 +Captain America,Marvel,5,2,7,Telekinesis,Kryptonite,0 +Batman,Marvel,8,5,2,Super Strength,Silver,1 +Spider-Man,DC Comics,5,4,6,Telekinesis,Magic,0 +Superman,Marvel,8,2,8,Invisibility,Silver,0 +Batman,DC Comics,10,9,7,Super Strength,Kryptonite,0 +Captain America,Marvel,1,9,7,Super Strength,Kryptonite,0 +Superman,Marvel,10,6,8,Telekinesis,Kryptonite,1 +Wonder Woman,Marvel,9,6,7,Super Strength,Silver,1 +Batman,DC Comics,6,8,5,Super Strength,Silver,1 +Wonder Woman,DC Comics,3,6,7,Super Strength,Silver,0 +Captain America,DC Comics,8,1,10,Flight,Magic,0 +Batman,Marvel,9,4,3,Flight,Wooden Stake,0 +Batman,Marvel,6,7,5,Super Strength,Wooden Stake,1 +Iron Man,Marvel,7,2,7,Flight,Kryptonite,0 +Superman,Marvel,1,9,9,Invisibility,Magic,1 +Flash,Marvel,5,8,2,Super Strength,Silver,0 +Superman,Marvel,5,8,4,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,10,7,7,Telekinesis,Magic,1 +Wonder Woman,DC Comics,4,4,1,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,6,2,2,Telekinesis,Magic,0 +Superman,DC Comics,7,3,9,Super Strength,Magic,1 +Superman,DC Comics,9,6,10,Telekinesis,Wooden Stake,0 +Batman,DC Comics,1,5,7,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,6,8,10,Invisibility,Silver,1 +Thor,Marvel,7,6,7,Invisibility,Wooden Stake,0 +Flash,Marvel,3,6,6,Invisibility,Wooden Stake,0 +Iron Man,Marvel,8,1,3,Super Strength,Silver,0 +Flash,DC Comics,5,4,10,Super Strength,Magic,1 +Spider-Man,Marvel,9,5,3,Invisibility,Silver,1 +Flash,Marvel,5,3,2,Super Strength,Kryptonite,0 +Iron Man,Marvel,9,9,6,Super Strength,Silver,1 +Spider-Man,DC Comics,10,1,4,Telekinesis,Magic,0 +Captain America,DC Comics,4,6,5,Telekinesis,Silver,0 +Batman,DC Comics,9,6,3,Invisibility,Magic,1 +Superman,DC Comics,5,10,6,Super Strength,Magic,1 +Superman,DC Comics,10,5,3,Telekinesis,Kryptonite,0 +Thor,Marvel,9,5,8,Flight,Silver,1 +Flash,DC Comics,3,10,9,Super Strength,Silver,1 +Wonder Woman,DC Comics,4,5,4,Flight,Kryptonite,0 +Wonder Woman,Marvel,9,6,9,Invisibility,Magic,1 +Iron Man,Marvel,10,8,7,Super Strength,Silver,1 +Iron Man,Marvel,6,2,3,Invisibility,Kryptonite,0 +Iron Man,DC Comics,2,6,7,Invisibility,Magic,1 +Wonder Woman,Marvel,7,1,1,Invisibility,Kryptonite,0 +Superman,DC Comics,2,4,3,Invisibility,Silver,0 +Wonder Woman,Marvel,2,10,6,Invisibility,Kryptonite,0 +Iron Man,DC Comics,1,3,4,Super Strength,Wooden Stake,0 +Batman,DC Comics,3,9,7,Flight,Magic,0 +Spider-Man,DC Comics,6,3,3,Super Strength,Wooden Stake,0 +Superman,DC Comics,8,6,1,Super Strength,Wooden Stake,1 +Batman,Marvel,9,1,9,Super Strength,Magic,0 +Captain America,Marvel,7,6,6,Telekinesis,Magic,0 +Flash,DC Comics,4,4,8,Telekinesis,Kryptonite,0 +Batman,Marvel,6,8,3,Super Strength,Magic,0 +Flash,DC Comics,5,9,8,Flight,Wooden Stake,1 +Batman,Marvel,8,4,2,Super Strength,Wooden Stake,0 +Captain America,Marvel,1,10,4,Invisibility,Silver,0 +Batman,DC Comics,1,10,3,Telekinesis,Magic,0 +Spider-Man,DC Comics,6,6,10,Telekinesis,Wooden Stake,1 +Superman,Marvel,10,1,1,Super Strength,Silver,0 +Flash,DC Comics,2,4,7,Super Strength,Silver,0 +Thor,Marvel,5,7,10,Flight,Kryptonite,0 +Wonder Woman,Marvel,1,1,2,Flight,Wooden Stake,0 +Captain America,Marvel,7,8,4,Invisibility,Kryptonite,0 +Flash,DC Comics,1,10,9,Super Strength,Wooden Stake,0 +Superman,DC Comics,4,6,6,Super Strength,Kryptonite,0 +Iron Man,Marvel,9,5,8,Super Strength,Kryptonite,0 +Flash,DC Comics,1,10,2,Telekinesis,Magic,0 +Spider-Man,DC Comics,4,9,7,Invisibility,Kryptonite,0 +Thor,Marvel,6,2,6,Flight,Magic,0 +Spider-Man,DC Comics,6,5,9,Telekinesis,Silver,0 +Flash,DC Comics,8,6,7,Telekinesis,Wooden Stake,0 +Spider-Man,Marvel,1,7,1,Telekinesis,Silver,0 +Iron Man,DC Comics,7,5,8,Telekinesis,Wooden Stake,0 +Thor,Marvel,1,9,10,Invisibility,Silver,1 +Wonder Woman,DC Comics,7,1,3,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,3,7,2,Flight,Kryptonite,0 +Iron Man,Marvel,8,10,3,Flight,Wooden Stake,0 +Captain America,Marvel,3,7,6,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,1,4,3,Telekinesis,Silver,0 +Batman,Marvel,8,9,10,Invisibility,Silver,1 +Flash,Marvel,3,5,5,Telekinesis,Silver,0 +Superman,DC Comics,2,4,6,Flight,Magic,0 +Flash,Marvel,1,7,8,Flight,Magic,0 +Flash,DC Comics,3,4,7,Super Strength,Wooden Stake,0 +Iron Man,DC Comics,2,3,8,Super Strength,Wooden Stake,0 +Iron Man,Marvel,2,9,3,Flight,Kryptonite,0 +Iron Man,DC Comics,6,8,4,Flight,Kryptonite,0 +Flash,Marvel,1,1,6,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,2,7,7,Invisibility,Magic,0 +Spider-Man,Marvel,6,9,9,Flight,Wooden Stake,1 +Wonder Woman,Marvel,3,8,1,Telekinesis,Kryptonite,0 +Thor,DC Comics,4,8,8,Super Strength,Magic,0 +Iron Man,Marvel,1,6,8,Flight,Magic,0 +Iron Man,Marvel,8,4,6,Telekinesis,Kryptonite,0 +Batman,Marvel,7,8,4,Flight,Wooden Stake,0 +Batman,DC Comics,7,3,3,Super Strength,Silver,1 +Captain America,DC Comics,3,9,3,Super Strength,Wooden Stake,0 +Captain America,Marvel,10,2,6,Invisibility,Wooden Stake,0 +Batman,Marvel,10,2,8,Invisibility,Kryptonite,0 +Thor,DC Comics,3,7,7,Invisibility,Magic,0 +Captain America,DC Comics,2,10,1,Invisibility,Kryptonite,0 +Superman,DC Comics,1,4,6,Super Strength,Wooden Stake,0 +Superman,Marvel,7,10,7,Telekinesis,Silver,1 +Thor,DC Comics,7,8,7,Telekinesis,Silver,1 +Batman,Marvel,2,9,9,Telekinesis,Silver,0 +Captain America,DC Comics,7,7,10,Flight,Kryptonite,0 +Iron Man,Marvel,8,5,5,Invisibility,Magic,1 +Batman,DC Comics,1,8,1,Invisibility,Kryptonite,0 +Captain America,Marvel,9,4,2,Super Strength,Silver,0 +Thor,DC Comics,7,2,4,Super Strength,Wooden Stake,1 +Superman,DC Comics,3,6,5,Flight,Magic,0 +Flash,Marvel,8,9,9,Flight,Kryptonite,0 +Thor,DC Comics,7,1,1,Telekinesis,Kryptonite,0 +Flash,DC Comics,8,10,3,Super Strength,Magic,1 +Captain America,DC Comics,6,7,5,Invisibility,Magic,0 +Thor,DC Comics,9,10,3,Telekinesis,Wooden Stake,0 +Captain America,Marvel,5,9,4,Invisibility,Magic,0 +Captain America,Marvel,3,10,3,Telekinesis,Wooden Stake,0 +Flash,DC Comics,3,9,4,Invisibility,Silver,1 +Thor,Marvel,1,10,1,Flight,Silver,0 +Spider-Man,Marvel,8,3,8,Telekinesis,Kryptonite,0 +Iron Man,Marvel,2,5,4,Invisibility,Silver,0 +Batman,Marvel,3,8,7,Invisibility,Silver,0 +Superman,Marvel,8,8,2,Super Strength,Wooden Stake,1 +Iron Man,DC Comics,8,4,2,Telekinesis,Kryptonite,0 +Batman,Marvel,4,1,6,Invisibility,Magic,1 +Batman,DC Comics,4,1,2,Super Strength,Kryptonite,0 +Superman,Marvel,5,4,6,Invisibility,Silver,1 +Iron Man,DC Comics,6,6,2,Telekinesis,Magic,0 +Superman,DC Comics,5,8,4,Flight,Kryptonite,0 +Captain America,DC Comics,7,6,7,Telekinesis,Kryptonite,0 +Superman,Marvel,2,9,8,Telekinesis,Kryptonite,0 +Flash,Marvel,7,9,3,Invisibility,Kryptonite,0 +Flash,DC Comics,10,2,9,Invisibility,Wooden Stake,1 +Thor,DC Comics,7,10,2,Telekinesis,Kryptonite,0 +Spider-Man,Marvel,1,1,8,Super Strength,Silver,0 +Spider-Man,Marvel,7,2,8,Super Strength,Silver,1 +Spider-Man,DC Comics,5,5,4,Super Strength,Wooden Stake,0 +Iron Man,Marvel,3,4,1,Invisibility,Magic,0 +Flash,Marvel,3,4,1,Invisibility,Magic,0 +Iron Man,Marvel,4,9,2,Telekinesis,Silver,0 +Captain America,Marvel,2,8,9,Flight,Silver,0 +Wonder Woman,Marvel,2,6,2,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,1,1,2,Telekinesis,Magic,0 +Captain America,DC Comics,5,2,6,Telekinesis,Magic,0 +Flash,DC Comics,4,6,7,Flight,Kryptonite,0 +Wonder Woman,DC Comics,10,2,7,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,2,10,9,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,3,5,6,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,7,5,8,Telekinesis,Silver,0 +Thor,Marvel,7,6,6,Super Strength,Wooden Stake,0 +Thor,Marvel,4,6,2,Super Strength,Magic,1 +Thor,DC Comics,5,6,1,Flight,Silver,0 +Superman,DC Comics,5,2,5,Invisibility,Kryptonite,0 +Thor,DC Comics,6,10,9,Super Strength,Wooden Stake,1 +Batman,Marvel,9,3,8,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,2,6,4,Invisibility,Kryptonite,0 +Thor,Marvel,5,8,5,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,3,1,5,Telekinesis,Kryptonite,0 +Flash,DC Comics,4,1,6,Flight,Magic,0 +Batman,DC Comics,10,2,3,Invisibility,Silver,0 +Batman,DC Comics,6,6,5,Telekinesis,Magic,0 +Batman,DC Comics,8,9,2,Super Strength,Magic,1 +Captain America,Marvel,1,4,10,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,10,3,1,Invisibility,Wooden Stake,0 +Captain America,DC Comics,8,8,1,Invisibility,Magic,0 +Batman,Marvel,7,10,10,Telekinesis,Magic,1 +Superman,Marvel,1,9,7,Telekinesis,Magic,0 +Thor,Marvel,2,5,2,Telekinesis,Wooden Stake,0 +Flash,Marvel,3,9,4,Invisibility,Wooden Stake,0 +Spider-Man,DC Comics,1,2,5,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,9,3,7,Flight,Magic,0 +Superman,DC Comics,8,7,2,Flight,Silver,0 +Iron Man,Marvel,2,7,6,Telekinesis,Wooden Stake,0 +Captain America,Marvel,9,6,1,Telekinesis,Kryptonite,0 +Thor,DC Comics,7,6,7,Super Strength,Magic,1 +Thor,DC Comics,9,2,9,Telekinesis,Silver,1 +Iron Man,Marvel,6,10,5,Flight,Wooden Stake,0 +Iron Man,Marvel,6,6,5,Flight,Silver,0 +Wonder Woman,DC Comics,4,4,4,Flight,Wooden Stake,0 +Thor,Marvel,10,3,3,Invisibility,Kryptonite,0 +Iron Man,Marvel,10,2,9,Invisibility,Silver,0 +Thor,DC Comics,2,1,5,Telekinesis,Magic,0 +Superman,Marvel,7,5,8,Super Strength,Magic,0 +Wonder Woman,Marvel,5,2,9,Super Strength,Wooden Stake,1 +Flash,Marvel,6,2,5,Super Strength,Magic,0 +Iron Man,Marvel,2,7,10,Invisibility,Silver,0 +Superman,Marvel,5,8,9,Flight,Kryptonite,0 +Superman,DC Comics,10,10,2,Flight,Wooden Stake,1 +Iron Man,Marvel,4,8,9,Invisibility,Silver,1 +Wonder Woman,DC Comics,9,4,4,Super Strength,Wooden Stake,1 +Thor,DC Comics,6,1,6,Super Strength,Kryptonite,0 +Flash,Marvel,2,7,6,Telekinesis,Wooden Stake,0 +Batman,DC Comics,1,1,6,Telekinesis,Magic,0 +Thor,Marvel,5,4,2,Super Strength,Magic,1 +Spider-Man,DC Comics,9,8,7,Invisibility,Wooden Stake,1 +Iron Man,DC Comics,6,2,6,Super Strength,Kryptonite,0 +Captain America,DC Comics,10,6,1,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,7,6,2,Super Strength,Magic,0 +Iron Man,DC Comics,5,9,7,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,10,5,1,Flight,Wooden Stake,1 +Superman,DC Comics,6,10,1,Invisibility,Silver,0 +Captain America,Marvel,5,4,1,Invisibility,Wooden Stake,0 +Captain America,Marvel,9,5,8,Telekinesis,Magic,1 +Thor,DC Comics,6,10,4,Invisibility,Magic,0 +Batman,DC Comics,8,5,4,Invisibility,Magic,0 +Thor,DC Comics,2,8,2,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,9,10,1,Telekinesis,Wooden Stake,0 +Captain America,Marvel,5,8,10,Flight,Silver,1 +Flash,Marvel,7,2,9,Super Strength,Wooden Stake,0 +Flash,Marvel,10,7,7,Invisibility,Silver,1 +Captain America,DC Comics,1,8,4,Telekinesis,Wooden Stake,0 +Flash,Marvel,10,6,6,Flight,Magic,1 +Flash,DC Comics,5,5,2,Super Strength,Silver,0 +Batman,DC Comics,10,9,7,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,2,3,2,Super Strength,Kryptonite,0 +Iron Man,Marvel,6,10,10,Super Strength,Kryptonite,1 +Batman,DC Comics,1,4,8,Invisibility,Wooden Stake,0 +Superman,Marvel,3,9,8,Invisibility,Magic,0 +Thor,DC Comics,5,6,1,Telekinesis,Silver,0 +Flash,Marvel,4,8,8,Super Strength,Wooden Stake,1 +Iron Man,DC Comics,3,7,2,Telekinesis,Kryptonite,0 +Thor,Marvel,10,2,6,Telekinesis,Silver,0 +Flash,DC Comics,5,3,1,Super Strength,Kryptonite,0 +Batman,Marvel,8,1,5,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,4,9,7,Super Strength,Wooden Stake,0 +Batman,DC Comics,1,7,10,Super Strength,Kryptonite,1 +Superman,DC Comics,7,1,1,Super Strength,Silver,0 +Spider-Man,Marvel,8,3,2,Super Strength,Magic,0 +Captain America,DC Comics,3,4,7,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,6,4,6,Super Strength,Silver,0 +Iron Man,DC Comics,2,5,3,Invisibility,Wooden Stake,0 +Captain America,Marvel,7,3,10,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,8,3,2,Invisibility,Kryptonite,0 +Iron Man,DC Comics,6,1,10,Super Strength,Silver,1 +Captain America,Marvel,6,7,4,Invisibility,Silver,1 +Captain America,DC Comics,5,10,3,Flight,Magic,0 +Iron Man,Marvel,8,1,7,Telekinesis,Silver,0 +Captain America,DC Comics,1,2,8,Super Strength,Silver,0 +Captain America,Marvel,10,4,2,Invisibility,Wooden Stake,0 +Iron Man,Marvel,4,4,10,Flight,Kryptonite,0 +Wonder Woman,Marvel,4,5,7,Telekinesis,Silver,1 +Captain America,DC Comics,3,2,8,Flight,Magic,0 +Captain America,DC Comics,3,4,6,Invisibility,Silver,0 +Wonder Woman,Marvel,4,1,6,Flight,Kryptonite,0 +Thor,DC Comics,1,2,10,Telekinesis,Silver,0 +Superman,DC Comics,2,1,1,Invisibility,Wooden Stake,0 +Thor,Marvel,9,10,4,Telekinesis,Kryptonite,0 +Flash,Marvel,10,10,1,Flight,Silver,0 +Spider-Man,Marvel,2,4,4,Super Strength,Wooden Stake,0 +Thor,Marvel,5,4,2,Super Strength,Kryptonite,0 +Thor,DC Comics,9,7,5,Super Strength,Silver,1 +Spider-Man,DC Comics,9,10,10,Super Strength,Wooden Stake,1 +Captain America,DC Comics,8,9,9,Telekinesis,Magic,0 +Captain America,DC Comics,1,9,10,Super Strength,Wooden Stake,1 +Thor,DC Comics,1,5,3,Telekinesis,Magic,0 +Spider-Man,DC Comics,9,10,8,Invisibility,Silver,1 +Captain America,Marvel,8,1,3,Super Strength,Wooden Stake,1 +Batman,DC Comics,10,1,6,Telekinesis,Magic,1 +Iron Man,DC Comics,9,6,4,Super Strength,Kryptonite,0 +Iron Man,DC Comics,7,2,8,Super Strength,Wooden Stake,0 +Superman,Marvel,3,8,6,Super Strength,Silver,1 +Iron Man,Marvel,3,9,8,Telekinesis,Kryptonite,0 +Thor,DC Comics,2,4,1,Flight,Magic,0 +Iron Man,Marvel,5,5,6,Super Strength,Wooden Stake,0 +Iron Man,Marvel,3,8,1,Super Strength,Wooden Stake,0 +Batman,DC Comics,6,3,1,Invisibility,Silver,0 +Captain America,DC Comics,2,5,8,Flight,Kryptonite,0 +Batman,DC Comics,3,3,7,Telekinesis,Wooden Stake,0 +Thor,Marvel,5,10,3,Invisibility,Wooden Stake,1 +Iron Man,Marvel,1,3,6,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,1,3,9,Invisibility,Wooden Stake,1 +Captain America,Marvel,10,7,7,Invisibility,Kryptonite,0 +Superman,Marvel,9,7,3,Super Strength,Kryptonite,1 +Superman,Marvel,7,7,6,Flight,Kryptonite,0 +Flash,DC Comics,1,10,4,Flight,Silver,0 +Flash,DC Comics,8,8,3,Invisibility,Kryptonite,0 +Iron Man,DC Comics,3,5,9,Super Strength,Kryptonite,0 +Iron Man,DC Comics,8,5,10,Telekinesis,Magic,1 +Superman,DC Comics,5,4,2,Invisibility,Magic,0 +Superman,Marvel,1,7,1,Telekinesis,Silver,0 +Wonder Woman,Marvel,7,10,2,Invisibility,Kryptonite,0 +Thor,Marvel,5,4,7,Invisibility,Magic,0 +Iron Man,Marvel,6,2,10,Super Strength,Magic,0 +Superman,Marvel,6,4,1,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,8,8,6,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,9,9,7,Telekinesis,Magic,1 +Superman,DC Comics,2,3,9,Flight,Silver,0 +Captain America,Marvel,9,7,8,Super Strength,Wooden Stake,1 +Captain America,DC Comics,10,9,6,Invisibility,Wooden Stake,1 +Spider-Man,Marvel,9,4,3,Invisibility,Kryptonite,0 +Flash,Marvel,10,10,8,Flight,Kryptonite,1 +Thor,DC Comics,10,3,7,Super Strength,Wooden Stake,1 +Flash,DC Comics,7,5,3,Invisibility,Silver,0 +Iron Man,Marvel,1,1,9,Flight,Kryptonite,0 +Flash,DC Comics,7,3,2,Flight,Kryptonite,0 +Iron Man,Marvel,10,8,3,Invisibility,Wooden Stake,1 +Superman,Marvel,5,8,2,Invisibility,Wooden Stake,1 +Captain America,Marvel,6,4,1,Telekinesis,Kryptonite,0 +Thor,Marvel,10,2,4,Super Strength,Magic,1 +Thor,Marvel,7,8,5,Telekinesis,Kryptonite,0 +Thor,DC Comics,5,8,6,Flight,Magic,0 +Superman,Marvel,7,10,5,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,9,4,1,Telekinesis,Magic,0 +Thor,Marvel,3,3,3,Flight,Silver,0 +Superman,DC Comics,8,2,1,Super Strength,Wooden Stake,0 +Superman,Marvel,2,9,5,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,7,1,5,Telekinesis,Kryptonite,0 +Batman,Marvel,2,7,6,Super Strength,Wooden Stake,0 +Flash,Marvel,4,5,8,Telekinesis,Wooden Stake,0 +Thor,DC Comics,7,8,10,Flight,Silver,1 +Batman,DC Comics,3,4,1,Super Strength,Wooden Stake,0 +Iron Man,DC Comics,2,7,4,Telekinesis,Kryptonite,0 +Superman,DC Comics,10,5,10,Super Strength,Silver,1 +Wonder Woman,DC Comics,7,5,1,Flight,Kryptonite,0 +Flash,DC Comics,1,9,9,Super Strength,Magic,0 +Flash,Marvel,8,9,7,Telekinesis,Wooden Stake,0 +Thor,Marvel,3,9,7,Flight,Magic,0 +Wonder Woman,Marvel,2,6,5,Invisibility,Kryptonite,0 +Captain America,DC Comics,3,6,7,Telekinesis,Magic,0 +Iron Man,DC Comics,5,5,2,Telekinesis,Magic,0 +Spider-Man,DC Comics,8,9,4,Flight,Kryptonite,0 +Spider-Man,Marvel,10,10,7,Flight,Kryptonite,0 +Batman,DC Comics,7,8,3,Invisibility,Wooden Stake,0 +Superman,Marvel,7,7,2,Telekinesis,Magic,0 +Batman,DC Comics,7,7,10,Flight,Silver,0 +Captain America,DC Comics,8,6,2,Invisibility,Silver,1 +Captain America,DC Comics,1,5,1,Invisibility,Kryptonite,0 +Flash,Marvel,4,4,5,Flight,Kryptonite,0 +Spider-Man,DC Comics,6,3,6,Telekinesis,Magic,1 +Wonder Woman,Marvel,9,3,6,Super Strength,Kryptonite,0 +Thor,DC Comics,2,6,9,Super Strength,Silver,1 +Spider-Man,DC Comics,1,4,4,Invisibility,Wooden Stake,0 +Spider-Man,DC Comics,10,6,1,Super Strength,Wooden Stake,0 +Wonder Woman,DC Comics,2,3,6,Super Strength,Magic,0 +Flash,Marvel,7,4,5,Flight,Wooden Stake,0 +Flash,DC Comics,3,9,10,Invisibility,Kryptonite,1 +Wonder Woman,Marvel,10,5,6,Telekinesis,Kryptonite,0 +Captain America,DC Comics,2,7,3,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,7,10,2,Flight,Kryptonite,0 +Batman,DC Comics,2,2,6,Super Strength,Magic,0 +Captain America,Marvel,3,5,1,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,7,9,7,Invisibility,Silver,0 +Superman,Marvel,4,3,7,Super Strength,Wooden Stake,0 +Captain America,Marvel,1,9,10,Invisibility,Kryptonite,0 +Captain America,DC Comics,5,6,7,Telekinesis,Silver,1 +Spider-Man,Marvel,9,4,10,Invisibility,Magic,0 +Thor,DC Comics,8,7,1,Invisibility,Kryptonite,0 +Spider-Man,Marvel,9,8,4,Invisibility,Kryptonite,1 +Iron Man,Marvel,10,6,7,Super Strength,Silver,1 +Captain America,Marvel,9,5,9,Telekinesis,Magic,0 +Wonder Woman,Marvel,7,6,5,Telekinesis,Silver,0 +Wonder Woman,DC Comics,4,5,2,Super Strength,Magic,0 +Wonder Woman,Marvel,5,8,7,Super Strength,Kryptonite,0 +Captain America,DC Comics,1,1,10,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,1,7,1,Flight,Kryptonite,0 +Iron Man,DC Comics,3,10,7,Invisibility,Wooden Stake,1 +Captain America,DC Comics,8,10,6,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,2,2,7,Telekinesis,Magic,0 +Captain America,Marvel,4,9,10,Invisibility,Silver,1 +Superman,DC Comics,2,1,3,Flight,Magic,0 +Captain America,Marvel,5,10,3,Super Strength,Kryptonite,0 +Iron Man,Marvel,9,6,7,Telekinesis,Silver,0 +Spider-Man,Marvel,1,9,2,Telekinesis,Wooden Stake,0 +Captain America,Marvel,5,1,1,Invisibility,Wooden Stake,0 +Thor,Marvel,9,4,9,Telekinesis,Kryptonite,1 +Iron Man,Marvel,1,4,9,Super Strength,Silver,0 +Batman,Marvel,9,9,7,Telekinesis,Kryptonite,0 +Superman,Marvel,8,5,7,Super Strength,Kryptonite,0 +Iron Man,Marvel,4,5,3,Flight,Magic,0 +Spider-Man,DC Comics,10,6,10,Flight,Kryptonite,0 +Wonder Woman,Marvel,5,1,2,Super Strength,Silver,1 +Wonder Woman,Marvel,5,1,7,Invisibility,Kryptonite,0 +Iron Man,Marvel,6,9,9,Telekinesis,Silver,0 +Batman,Marvel,7,3,1,Invisibility,Wooden Stake,0 +Wonder Woman,Marvel,8,4,4,Telekinesis,Kryptonite,0 +Superman,DC Comics,8,1,6,Flight,Silver,0 +Thor,DC Comics,2,9,7,Flight,Wooden Stake,0 +Batman,Marvel,9,8,10,Flight,Silver,1 +Flash,DC Comics,7,2,7,Telekinesis,Wooden Stake,0 +Flash,Marvel,4,8,10,Flight,Magic,0 +Iron Man,Marvel,4,7,2,Flight,Kryptonite,0 +Batman,DC Comics,8,6,4,Flight,Kryptonite,0 +Wonder Woman,DC Comics,4,1,5,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,6,7,1,Invisibility,Magic,1 +Iron Man,DC Comics,5,10,1,Flight,Silver,0 +Wonder Woman,DC Comics,3,7,10,Flight,Magic,0 +Wonder Woman,Marvel,10,9,3,Invisibility,Silver,1 +Thor,Marvel,2,1,10,Invisibility,Silver,0 +Thor,Marvel,9,2,3,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,10,9,8,Super Strength,Wooden Stake,1 +Thor,Marvel,9,9,9,Flight,Kryptonite,0 +Captain America,DC Comics,1,6,1,Flight,Kryptonite,0 +Batman,Marvel,10,6,2,Flight,Kryptonite,0 +Batman,DC Comics,3,4,10,Telekinesis,Silver,0 +Iron Man,DC Comics,8,4,2,Flight,Kryptonite,0 +Thor,Marvel,6,5,4,Super Strength,Silver,1 +Spider-Man,Marvel,5,3,2,Invisibility,Wooden Stake,0 +Wonder Woman,Marvel,5,1,7,Telekinesis,Silver,0 +Spider-Man,Marvel,6,1,9,Invisibility,Silver,0 +Spider-Man,DC Comics,7,7,7,Flight,Magic,1 +Superman,Marvel,1,1,6,Flight,Kryptonite,0 +Wonder Woman,DC Comics,9,1,10,Flight,Kryptonite,0 +Captain America,Marvel,3,3,1,Super Strength,Kryptonite,0 +Thor,Marvel,4,10,10,Super Strength,Kryptonite,1 +Wonder Woman,Marvel,10,4,9,Telekinesis,Magic,1 +Spider-Man,Marvel,1,4,5,Invisibility,Magic,0 +Wonder Woman,Marvel,10,2,5,Flight,Magic,0 +Captain America,DC Comics,3,1,6,Flight,Magic,0 +Batman,Marvel,2,3,9,Flight,Kryptonite,0 +Iron Man,DC Comics,2,4,8,Flight,Silver,0 +Thor,Marvel,1,3,8,Super Strength,Wooden Stake,0 +Thor,DC Comics,8,8,8,Invisibility,Magic,0 +Superman,Marvel,3,10,1,Invisibility,Silver,0 +Batman,Marvel,3,1,1,Telekinesis,Magic,0 +Thor,Marvel,6,2,8,Super Strength,Kryptonite,0 +Superman,DC Comics,8,7,5,Flight,Kryptonite,1 +Superman,DC Comics,9,4,9,Invisibility,Silver,1 +Superman,Marvel,9,8,2,Invisibility,Silver,1 +Flash,Marvel,4,3,9,Super Strength,Silver,1 +Thor,Marvel,5,6,8,Telekinesis,Kryptonite,0 +Thor,DC Comics,2,9,9,Telekinesis,Kryptonite,0 +Thor,Marvel,9,1,4,Flight,Wooden Stake,0 +Captain America,DC Comics,8,1,1,Telekinesis,Silver,0 +Superman,Marvel,3,8,1,Invisibility,Wooden Stake,0 +Captain America,DC Comics,9,3,5,Telekinesis,Magic,1 +Iron Man,DC Comics,3,5,2,Flight,Wooden Stake,0 +Thor,DC Comics,9,1,8,Invisibility,Magic,1 +Flash,Marvel,2,5,10,Telekinesis,Magic,0 +Wonder Woman,DC Comics,10,6,5,Telekinesis,Wooden Stake,1 +Batman,Marvel,9,8,5,Super Strength,Silver,1 +Flash,DC Comics,8,3,2,Flight,Magic,0 +Spider-Man,Marvel,9,3,7,Telekinesis,Silver,0 +Iron Man,DC Comics,5,10,8,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,2,9,10,Invisibility,Magic,1 +Spider-Man,Marvel,8,4,1,Super Strength,Kryptonite,0 +Spider-Man,Marvel,6,4,2,Super Strength,Wooden Stake,1 +Thor,DC Comics,8,7,10,Telekinesis,Silver,1 +Batman,DC Comics,5,2,4,Telekinesis,Wooden Stake,0 +Spider-Man,Marvel,10,8,5,Telekinesis,Magic,1 +Superman,DC Comics,2,6,2,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,6,3,1,Invisibility,Magic,0 +Flash,Marvel,5,9,9,Flight,Wooden Stake,0 +Flash,Marvel,5,5,1,Super Strength,Silver,0 +Spider-Man,Marvel,1,8,4,Telekinesis,Silver,0 +Iron Man,DC Comics,2,7,2,Flight,Magic,0 +Batman,DC Comics,8,8,4,Invisibility,Magic,0 +Batman,DC Comics,3,7,8,Flight,Kryptonite,0 +Flash,Marvel,10,3,8,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,3,2,9,Super Strength,Magic,0 +Batman,Marvel,8,7,5,Super Strength,Kryptonite,0 +Iron Man,Marvel,8,3,7,Telekinesis,Magic,0 +Flash,DC Comics,2,3,3,Super Strength,Silver,0 +Wonder Woman,Marvel,8,2,10,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,1,4,4,Super Strength,Kryptonite,0 +Iron Man,Marvel,6,8,10,Super Strength,Magic,1 +Superman,Marvel,8,1,9,Super Strength,Wooden Stake,1 +Thor,Marvel,3,1,10,Invisibility,Silver,0 +Spider-Man,DC Comics,8,5,10,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,1,5,1,Telekinesis,Kryptonite,0 +Flash,DC Comics,9,1,2,Invisibility,Wooden Stake,0 +Batman,Marvel,9,6,5,Telekinesis,Kryptonite,0 +Iron Man,Marvel,5,1,3,Flight,Wooden Stake,0 +Flash,Marvel,10,5,2,Flight,Magic,1 +Spider-Man,DC Comics,4,9,1,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,6,5,10,Flight,Kryptonite,0 +Wonder Woman,DC Comics,7,6,3,Flight,Silver,1 +Spider-Man,DC Comics,5,8,1,Super Strength,Silver,0 +Thor,DC Comics,10,1,1,Super Strength,Silver,0 +Superman,Marvel,9,2,1,Telekinesis,Kryptonite,0 +Batman,Marvel,3,9,8,Flight,Wooden Stake,1 +Superman,DC Comics,7,3,3,Telekinesis,Silver,0 +Wonder Woman,DC Comics,10,6,1,Telekinesis,Silver,0 +Batman,DC Comics,10,5,7,Flight,Silver,1 +Wonder Woman,DC Comics,5,2,10,Invisibility,Magic,1 +Iron Man,Marvel,7,7,3,Flight,Kryptonite,0 +Iron Man,DC Comics,2,4,8,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,4,1,4,Flight,Kryptonite,0 +Batman,DC Comics,2,4,4,Invisibility,Kryptonite,0 +Batman,DC Comics,7,6,5,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,2,7,6,Telekinesis,Magic,0 +Superman,Marvel,1,7,7,Super Strength,Wooden Stake,0 +Iron Man,DC Comics,9,7,4,Super Strength,Magic,1 +Captain America,Marvel,1,3,8,Super Strength,Silver,0 +Spider-Man,Marvel,8,6,6,Telekinesis,Magic,0 +Flash,DC Comics,2,8,1,Super Strength,Kryptonite,0 +Batman,DC Comics,8,4,1,Flight,Magic,0 +Thor,Marvel,3,8,9,Telekinesis,Kryptonite,0 +Thor,Marvel,6,2,10,Invisibility,Magic,0 +Captain America,Marvel,3,10,6,Telekinesis,Kryptonite,0 +Iron Man,Marvel,7,9,10,Flight,Silver,1 +Iron Man,Marvel,10,9,8,Flight,Kryptonite,0 +Iron Man,DC Comics,9,8,7,Super Strength,Magic,1 +Superman,Marvel,2,10,6,Telekinesis,Silver,0 +Wonder Woman,Marvel,5,10,4,Telekinesis,Magic,1 +Thor,Marvel,6,1,7,Telekinesis,Silver,0 +Iron Man,Marvel,4,2,9,Invisibility,Wooden Stake,0 +Thor,Marvel,4,6,10,Super Strength,Wooden Stake,0 +Captain America,Marvel,4,10,10,Flight,Wooden Stake,0 +Spider-Man,Marvel,2,5,7,Flight,Magic,0 +Wonder Woman,Marvel,4,9,1,Super Strength,Magic,1 +Superman,DC Comics,1,5,10,Flight,Silver,1 +Batman,DC Comics,6,2,9,Flight,Silver,0 +Captain America,Marvel,1,10,4,Super Strength,Silver,0 +Wonder Woman,DC Comics,10,4,3,Flight,Silver,0 +Thor,DC Comics,6,9,4,Telekinesis,Kryptonite,0 +Captain America,DC Comics,1,1,4,Invisibility,Wooden Stake,0 +Batman,DC Comics,6,1,10,Super Strength,Kryptonite,1 +Wonder Woman,DC Comics,10,7,2,Invisibility,Kryptonite,0 +Superman,DC Comics,8,3,1,Flight,Kryptonite,0 +Flash,Marvel,2,10,10,Flight,Kryptonite,0 +Spider-Man,Marvel,2,2,1,Telekinesis,Wooden Stake,0 +Batman,DC Comics,4,9,8,Super Strength,Kryptonite,1 +Wonder Woman,Marvel,3,3,2,Flight,Silver,0 +Superman,DC Comics,4,2,10,Super Strength,Magic,1 +Thor,Marvel,7,8,5,Super Strength,Silver,1 +Batman,Marvel,1,10,4,Super Strength,Magic,0 +Flash,Marvel,6,6,8,Super Strength,Silver,1 +Captain America,DC Comics,3,6,2,Super Strength,Silver,0 +Iron Man,Marvel,10,10,10,Invisibility,Magic,1 +Captain America,Marvel,7,7,9,Telekinesis,Wooden Stake,1 +Thor,DC Comics,10,7,7,Super Strength,Kryptonite,1 +Wonder Woman,DC Comics,2,6,7,Invisibility,Silver,0 +Flash,Marvel,2,4,1,Flight,Wooden Stake,0 +Spider-Man,DC Comics,4,9,2,Super Strength,Kryptonite,0 +Batman,Marvel,1,6,4,Flight,Wooden Stake,0 +Wonder Woman,Marvel,3,4,4,Super Strength,Wooden Stake,0 +Spider-Man,DC Comics,9,3,3,Invisibility,Kryptonite,0 +Thor,DC Comics,7,4,7,Invisibility,Silver,0 +Batman,Marvel,7,3,8,Invisibility,Wooden Stake,1 +Superman,DC Comics,4,2,2,Telekinesis,Silver,0 +Superman,Marvel,2,5,4,Flight,Silver,0 +Wonder Woman,DC Comics,4,2,3,Telekinesis,Silver,0 +Captain America,DC Comics,6,6,2,Super Strength,Kryptonite,0 +Wonder Woman,DC Comics,3,3,6,Flight,Magic,0 +Captain America,DC Comics,1,6,4,Invisibility,Silver,0 +Flash,DC Comics,8,10,6,Flight,Magic,1 +Thor,Marvel,5,9,2,Invisibility,Magic,0 +Superman,Marvel,5,1,4,Telekinesis,Wooden Stake,0 +Flash,Marvel,4,6,6,Telekinesis,Silver,0 +Batman,DC Comics,6,9,5,Invisibility,Silver,1 +Superman,Marvel,3,4,3,Invisibility,Silver,0 +Captain America,Marvel,9,2,8,Super Strength,Magic,1 +Wonder Woman,DC Comics,5,4,7,Telekinesis,Kryptonite,0 +Thor,DC Comics,3,1,3,Telekinesis,Magic,0 +Superman,DC Comics,1,3,6,Super Strength,Silver,1 +Flash,Marvel,10,10,4,Telekinesis,Silver,1 +Thor,Marvel,6,9,5,Invisibility,Silver,0 +Flash,DC Comics,2,10,5,Flight,Magic,1 +Superman,Marvel,3,5,7,Flight,Silver,0 +Wonder Woman,Marvel,1,6,5,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,9,3,3,Super Strength,Silver,1 +Wonder Woman,Marvel,8,5,10,Invisibility,Kryptonite,0 +Superman,DC Comics,2,8,5,Flight,Wooden Stake,0 +Captain America,Marvel,8,6,7,Invisibility,Silver,0 +Wonder Woman,DC Comics,9,4,5,Telekinesis,Wooden Stake,0 +Batman,Marvel,1,2,5,Telekinesis,Silver,0 +Captain America,Marvel,5,9,9,Flight,Kryptonite,0 +Captain America,DC Comics,8,1,3,Telekinesis,Silver,0 +Captain America,DC Comics,2,1,6,Super Strength,Wooden Stake,1 +Thor,DC Comics,4,4,1,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,7,7,10,Telekinesis,Magic,1 +Iron Man,Marvel,3,1,5,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,5,9,8,Invisibility,Kryptonite,0 +Flash,DC Comics,8,4,5,Invisibility,Kryptonite,0 +Flash,DC Comics,10,3,9,Flight,Wooden Stake,1 +Captain America,DC Comics,3,1,6,Flight,Kryptonite,0 +Iron Man,DC Comics,4,10,8,Flight,Silver,1 +Spider-Man,Marvel,9,4,10,Telekinesis,Kryptonite,1 +Thor,DC Comics,7,9,8,Invisibility,Kryptonite,0 +Captain America,DC Comics,1,10,3,Super Strength,Silver,0 +Batman,DC Comics,4,6,7,Telekinesis,Silver,1 +Thor,Marvel,4,6,7,Telekinesis,Magic,0 +Spider-Man,Marvel,9,1,10,Telekinesis,Kryptonite,0 +Thor,Marvel,6,10,6,Super Strength,Wooden Stake,1 +Batman,DC Comics,9,2,7,Flight,Kryptonite,0 +Flash,DC Comics,6,6,2,Super Strength,Kryptonite,0 +Thor,Marvel,6,2,9,Flight,Silver,1 +Spider-Man,Marvel,5,3,10,Super Strength,Magic,1 +Flash,DC Comics,5,4,10,Invisibility,Kryptonite,0 +Flash,DC Comics,2,5,1,Telekinesis,Wooden Stake,0 +Flash,DC Comics,8,9,1,Telekinesis,Kryptonite,0 +Batman,Marvel,8,4,3,Telekinesis,Wooden Stake,1 +Batman,DC Comics,1,9,3,Flight,Silver,0 +Flash,DC Comics,8,10,1,Super Strength,Magic,1 +Thor,Marvel,5,3,7,Invisibility,Kryptonite,0 +Batman,Marvel,2,8,4,Super Strength,Magic,0 +Wonder Woman,Marvel,2,1,10,Telekinesis,Kryptonite,0 +Thor,DC Comics,6,9,2,Invisibility,Wooden Stake,0 +Captain America,Marvel,9,9,10,Invisibility,Magic,1 +Batman,Marvel,1,10,5,Telekinesis,Kryptonite,0 +Thor,DC Comics,6,2,6,Super Strength,Silver,1 +Captain America,DC Comics,9,4,9,Telekinesis,Wooden Stake,1 +Batman,Marvel,8,8,4,Super Strength,Magic,1 +Captain America,DC Comics,6,7,2,Invisibility,Kryptonite,0 +Superman,Marvel,3,1,5,Invisibility,Magic,0 +Batman,DC Comics,8,5,3,Telekinesis,Kryptonite,0 +Superman,DC Comics,9,7,2,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,1,4,1,Flight,Silver,0 +Spider-Man,Marvel,9,1,10,Invisibility,Wooden Stake,1 +Thor,Marvel,6,9,2,Flight,Magic,0 +Iron Man,DC Comics,6,5,6,Invisibility,Magic,1 +Superman,Marvel,4,2,8,Telekinesis,Kryptonite,0 +Superman,DC Comics,1,8,3,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,10,2,9,Flight,Kryptonite,0 +Superman,Marvel,8,3,9,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,2,10,2,Invisibility,Magic,0 +Flash,DC Comics,1,1,8,Invisibility,Kryptonite,0 +Captain America,Marvel,2,2,10,Telekinesis,Kryptonite,0 +Captain America,DC Comics,1,7,5,Invisibility,Wooden Stake,0 +Iron Man,DC Comics,1,10,4,Super Strength,Silver,0 +Superman,Marvel,9,2,10,Super Strength,Wooden Stake,1 +Superman,Marvel,1,6,5,Invisibility,Silver,1 +Superman,DC Comics,4,3,4,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,10,4,8,Flight,Magic,1 +Thor,DC Comics,6,8,4,Telekinesis,Kryptonite,0 +Batman,DC Comics,7,3,10,Flight,Wooden Stake,1 +Iron Man,Marvel,2,10,6,Telekinesis,Magic,0 +Iron Man,DC Comics,6,6,2,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,7,1,5,Super Strength,Kryptonite,0 +Iron Man,DC Comics,10,7,6,Telekinesis,Wooden Stake,1 +Flash,DC Comics,10,8,5,Flight,Silver,1 +Flash,Marvel,2,8,2,Super Strength,Kryptonite,0 +Iron Man,DC Comics,2,3,7,Flight,Silver,0 +Wonder Woman,Marvel,10,10,4,Invisibility,Magic,1 +Iron Man,Marvel,7,1,8,Super Strength,Magic,0 +Superman,Marvel,1,9,7,Flight,Wooden Stake,0 +Wonder Woman,Marvel,8,6,7,Telekinesis,Silver,0 +Thor,Marvel,3,9,9,Invisibility,Silver,1 +Spider-Man,DC Comics,6,7,1,Invisibility,Kryptonite,0 +Superman,Marvel,9,1,10,Invisibility,Silver,0 +Flash,Marvel,6,1,6,Telekinesis,Silver,0 +Superman,Marvel,9,6,6,Telekinesis,Kryptonite,0 +Batman,DC Comics,7,5,6,Super Strength,Kryptonite,0 +Wonder Woman,Marvel,9,9,6,Telekinesis,Silver,1 +Flash,DC Comics,2,2,10,Super Strength,Wooden Stake,0 +Spider-Man,Marvel,8,8,7,Invisibility,Kryptonite,0 +Iron Man,Marvel,8,5,10,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,2,2,6,Flight,Silver,0 +Thor,DC Comics,4,10,1,Invisibility,Silver,0 +Captain America,DC Comics,7,6,3,Invisibility,Kryptonite,0 +Superman,Marvel,4,10,2,Super Strength,Silver,0 +Wonder Woman,DC Comics,4,8,6,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,6,4,8,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,10,2,3,Flight,Wooden Stake,0 +Batman,DC Comics,6,5,10,Super Strength,Kryptonite,0 +Flash,DC Comics,10,2,8,Super Strength,Kryptonite,1 +Thor,Marvel,3,2,8,Invisibility,Magic,0 +Captain America,DC Comics,9,6,5,Telekinesis,Magic,0 +Thor,Marvel,10,10,8,Invisibility,Silver,1 +Wonder Woman,DC Comics,2,9,6,Invisibility,Silver,0 +Iron Man,DC Comics,6,4,5,Super Strength,Kryptonite,0 +Captain America,Marvel,7,6,9,Invisibility,Kryptonite,0 +Flash,Marvel,9,7,7,Flight,Magic,1 +Flash,Marvel,3,6,8,Invisibility,Magic,0 +Wonder Woman,Marvel,10,8,1,Invisibility,Kryptonite,0 +Batman,DC Comics,3,4,2,Super Strength,Wooden Stake,0 +Captain America,Marvel,7,1,8,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,4,7,9,Telekinesis,Silver,1 +Batman,DC Comics,8,3,4,Super Strength,Kryptonite,0 +Iron Man,DC Comics,7,6,10,Invisibility,Kryptonite,1 +Batman,Marvel,5,2,10,Flight,Silver,0 +Thor,Marvel,7,9,9,Flight,Magic,1 +Spider-Man,Marvel,3,1,4,Super Strength,Magic,0 +Thor,DC Comics,2,6,10,Super Strength,Wooden Stake,1 +Flash,Marvel,6,6,10,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,2,5,10,Telekinesis,Magic,0 +Wonder Woman,DC Comics,3,5,9,Invisibility,Wooden Stake,0 +Superman,Marvel,6,1,7,Flight,Wooden Stake,0 +Thor,DC Comics,5,10,2,Telekinesis,Wooden Stake,0 +Captain America,Marvel,8,5,9,Telekinesis,Magic,1 +Flash,Marvel,9,2,4,Telekinesis,Magic,0 +Iron Man,Marvel,3,7,8,Invisibility,Kryptonite,0 +Flash,Marvel,10,3,7,Flight,Kryptonite,0 +Superman,Marvel,3,4,7,Super Strength,Wooden Stake,1 +Superman,DC Comics,3,3,8,Invisibility,Wooden Stake,0 +Superman,Marvel,6,3,1,Super Strength,Magic,0 +Wonder Woman,Marvel,1,4,5,Telekinesis,Magic,0 +Spider-Man,Marvel,7,5,2,Telekinesis,Kryptonite,0 +Batman,Marvel,1,1,2,Invisibility,Kryptonite,0 +Captain America,Marvel,5,4,1,Flight,Silver,0 +Flash,Marvel,10,8,5,Telekinesis,Kryptonite,0 +Wonder Woman,Marvel,8,10,2,Super Strength,Magic,1 +Flash,DC Comics,4,7,4,Super Strength,Wooden Stake,1 +Iron Man,DC Comics,5,9,3,Invisibility,Silver,1 +Wonder Woman,Marvel,4,5,3,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,4,10,2,Flight,Kryptonite,0 +Flash,Marvel,8,4,6,Telekinesis,Magic,1 +Wonder Woman,DC Comics,2,8,2,Super Strength,Silver,1 +Wonder Woman,Marvel,1,9,8,Super Strength,Kryptonite,0 +Thor,Marvel,3,7,8,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,9,7,5,Invisibility,Magic,1 +Superman,Marvel,4,5,10,Super Strength,Silver,0 +Iron Man,DC Comics,10,4,7,Invisibility,Kryptonite,0 +Iron Man,Marvel,5,10,4,Invisibility,Kryptonite,0 +Thor,Marvel,2,1,1,Super Strength,Silver,0 +Batman,Marvel,4,10,2,Flight,Magic,0 +Wonder Woman,Marvel,2,10,10,Invisibility,Silver,0 +Captain America,DC Comics,2,7,10,Super Strength,Silver,1 +Superman,Marvel,4,1,4,Invisibility,Magic,0 +Flash,DC Comics,6,1,1,Telekinesis,Kryptonite,0 +Batman,DC Comics,7,5,8,Flight,Wooden Stake,0 +Spider-Man,Marvel,10,9,9,Flight,Magic,1 +Wonder Woman,Marvel,3,6,4,Telekinesis,Wooden Stake,0 +Superman,DC Comics,3,3,10,Telekinesis,Kryptonite,0 +Captain America,DC Comics,10,3,3,Invisibility,Silver,0 +Wonder Woman,Marvel,6,7,2,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,3,6,5,Flight,Kryptonite,0 +Thor,DC Comics,2,9,3,Telekinesis,Kryptonite,0 +Batman,DC Comics,8,6,10,Super Strength,Silver,1 +Wonder Woman,Marvel,5,5,7,Super Strength,Silver,0 +Superman,DC Comics,1,10,6,Invisibility,Kryptonite,0 +Iron Man,DC Comics,3,7,1,Flight,Kryptonite,0 +Flash,DC Comics,10,1,8,Super Strength,Wooden Stake,1 +Flash,DC Comics,8,7,2,Telekinesis,Kryptonite,0 +Flash,Marvel,4,3,5,Super Strength,Kryptonite,0 +Captain America,Marvel,7,9,9,Super Strength,Wooden Stake,1 +Wonder Woman,DC Comics,10,6,8,Invisibility,Magic,1 +Flash,DC Comics,2,9,2,Telekinesis,Wooden Stake,0 +Superman,DC Comics,7,5,9,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,5,7,5,Telekinesis,Silver,0 +Superman,Marvel,5,4,10,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,6,7,6,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,9,1,3,Telekinesis,Kryptonite,0 +Iron Man,Marvel,6,7,3,Super Strength,Kryptonite,0 +Iron Man,DC Comics,8,8,10,Super Strength,Magic,1 +Superman,DC Comics,7,5,8,Telekinesis,Kryptonite,0 +Thor,Marvel,9,2,10,Flight,Magic,1 +Wonder Woman,Marvel,4,5,10,Flight,Kryptonite,0 +Flash,Marvel,2,6,2,Telekinesis,Wooden Stake,0 +Thor,Marvel,7,2,2,Flight,Silver,0 +Batman,Marvel,6,6,5,Invisibility,Kryptonite,0 +Flash,DC Comics,1,6,6,Super Strength,Magic,0 +Spider-Man,Marvel,9,1,2,Invisibility,Magic,1 +Thor,Marvel,9,1,5,Super Strength,Silver,1 +Superman,Marvel,2,10,7,Flight,Kryptonite,0 +Wonder Woman,Marvel,3,3,10,Flight,Wooden Stake,0 +Thor,Marvel,5,10,10,Telekinesis,Kryptonite,0 +Batman,Marvel,5,10,8,Flight,Kryptonite,0 +Captain America,DC Comics,1,3,7,Flight,Silver,0 +Batman,Marvel,8,4,8,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,8,2,9,Telekinesis,Wooden Stake,0 +Flash,DC Comics,4,9,5,Super Strength,Magic,1 +Wonder Woman,Marvel,7,10,5,Flight,Silver,0 +Iron Man,Marvel,10,7,10,Super Strength,Wooden Stake,1 +Thor,DC Comics,3,7,4,Super Strength,Magic,1 +Thor,DC Comics,6,6,9,Invisibility,Silver,0 +Batman,DC Comics,10,3,5,Flight,Silver,0 +Batman,Marvel,10,6,2,Flight,Magic,1 +Superman,DC Comics,9,8,10,Invisibility,Magic,1 +Spider-Man,Marvel,1,8,8,Super Strength,Wooden Stake,1 +Superman,Marvel,5,9,7,Flight,Kryptonite,0 +Iron Man,DC Comics,4,1,8,Super Strength,Kryptonite,0 +Superman,Marvel,8,1,3,Invisibility,Kryptonite,0 +Batman,Marvel,1,3,4,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,9,3,5,Super Strength,Kryptonite,0 +Superman,DC Comics,6,10,6,Flight,Wooden Stake,0 +Captain America,Marvel,4,8,1,Telekinesis,Silver,0 +Flash,DC Comics,9,10,4,Super Strength,Wooden Stake,1 +Spider-Man,Marvel,5,1,10,Super Strength,Wooden Stake,1 +Batman,DC Comics,5,2,5,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,5,2,7,Telekinesis,Silver,1 +Thor,DC Comics,1,3,5,Telekinesis,Wooden Stake,0 +Flash,DC Comics,1,6,1,Flight,Wooden Stake,0 +Superman,Marvel,8,1,7,Flight,Silver,0 +Batman,DC Comics,8,2,8,Super Strength,Wooden Stake,1 +Thor,Marvel,6,1,7,Super Strength,Kryptonite,0 +Thor,Marvel,4,5,4,Invisibility,Magic,0 +Iron Man,DC Comics,2,7,8,Flight,Wooden Stake,0 +Iron Man,DC Comics,2,8,5,Super Strength,Magic,1 +Wonder Woman,DC Comics,9,10,10,Telekinesis,Wooden Stake,0 +Batman,DC Comics,5,1,9,Telekinesis,Wooden Stake,0 +Flash,DC Comics,4,7,10,Flight,Kryptonite,0 +Wonder Woman,Marvel,10,5,5,Telekinesis,Silver,0 +Batman,DC Comics,1,10,1,Invisibility,Magic,0 +Captain America,Marvel,7,1,9,Super Strength,Silver,1 +Spider-Man,Marvel,3,3,5,Super Strength,Kryptonite,0 +Spider-Man,Marvel,6,7,6,Super Strength,Kryptonite,0 +Flash,Marvel,5,10,4,Flight,Magic,0 +Batman,DC Comics,5,1,6,Telekinesis,Silver,0 +Iron Man,DC Comics,5,7,8,Invisibility,Kryptonite,0 +Flash,Marvel,1,5,3,Flight,Wooden Stake,0 +Superman,Marvel,1,1,5,Super Strength,Wooden Stake,0 +Wonder Woman,DC Comics,3,1,2,Invisibility,Wooden Stake,0 +Captain America,Marvel,10,1,2,Super Strength,Silver,0 +Spider-Man,DC Comics,4,9,7,Super Strength,Wooden Stake,0 +Batman,Marvel,5,3,10,Flight,Wooden Stake,1 +Iron Man,DC Comics,2,5,10,Super Strength,Kryptonite,0 +Iron Man,Marvel,8,10,10,Invisibility,Kryptonite,0 +Iron Man,Marvel,2,9,6,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,9,6,4,Telekinesis,Wooden Stake,1 +Superman,DC Comics,2,9,5,Super Strength,Kryptonite,0 +Thor,DC Comics,9,8,1,Flight,Magic,0 +Flash,DC Comics,7,8,7,Invisibility,Silver,1 +Wonder Woman,Marvel,8,1,8,Flight,Silver,0 +Superman,Marvel,2,9,9,Telekinesis,Kryptonite,0 +Iron Man,Marvel,7,6,8,Super Strength,Silver,1 +Batman,Marvel,6,9,5,Flight,Kryptonite,0 +Flash,Marvel,4,3,3,Flight,Kryptonite,0 +Captain America,Marvel,7,3,10,Flight,Kryptonite,0 +Superman,DC Comics,4,6,9,Flight,Kryptonite,0 +Batman,DC Comics,2,9,6,Telekinesis,Magic,0 +Wonder Woman,DC Comics,10,7,5,Telekinesis,Wooden Stake,1 +Wonder Woman,Marvel,7,3,3,Super Strength,Wooden Stake,0 +Flash,DC Comics,8,3,6,Super Strength,Magic,0 +Iron Man,Marvel,2,2,3,Invisibility,Silver,0 +Captain America,Marvel,5,9,10,Telekinesis,Silver,0 +Spider-Man,DC Comics,1,3,6,Flight,Wooden Stake,0 +Spider-Man,Marvel,7,5,4,Flight,Silver,1 +Wonder Woman,Marvel,8,9,2,Invisibility,Wooden Stake,1 +Batman,Marvel,6,8,8,Flight,Wooden Stake,1 +Captain America,Marvel,5,2,4,Invisibility,Magic,0 +Batman,Marvel,6,3,9,Super Strength,Silver,1 +Captain America,DC Comics,2,2,7,Telekinesis,Magic,0 +Captain America,DC Comics,1,8,2,Invisibility,Wooden Stake,0 +Wonder Woman,Marvel,7,6,4,Flight,Wooden Stake,0 +Batman,Marvel,7,6,5,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,10,9,3,Super Strength,Kryptonite,0 +Flash,DC Comics,10,8,9,Flight,Kryptonite,0 +Captain America,DC Comics,2,4,5,Super Strength,Kryptonite,0 +Superman,Marvel,2,4,2,Super Strength,Magic,0 +Iron Man,DC Comics,1,9,3,Invisibility,Wooden Stake,0 +Flash,DC Comics,10,1,9,Super Strength,Silver,1 +Captain America,Marvel,8,2,7,Flight,Magic,1 +Superman,Marvel,8,2,2,Super Strength,Magic,0 +Captain America,DC Comics,1,6,9,Super Strength,Magic,0 +Superman,Marvel,8,4,4,Invisibility,Silver,0 +Batman,DC Comics,9,10,9,Super Strength,Wooden Stake,1 +Spider-Man,DC Comics,4,3,2,Telekinesis,Kryptonite,0 +Thor,Marvel,1,3,10,Invisibility,Wooden Stake,0 +Flash,Marvel,1,3,4,Invisibility,Wooden Stake,0 +Captain America,DC Comics,3,6,5,Flight,Magic,0 +Thor,Marvel,5,8,2,Flight,Magic,0 +Captain America,Marvel,5,7,10,Flight,Magic,1 +Batman,Marvel,9,4,1,Flight,Kryptonite,0 +Batman,Marvel,10,4,7,Telekinesis,Kryptonite,0 +Superman,Marvel,2,10,10,Invisibility,Kryptonite,0 +Captain America,Marvel,2,2,1,Super Strength,Wooden Stake,0 +Batman,Marvel,6,1,8,Flight,Magic,0 +Batman,DC Comics,9,9,3,Flight,Silver,1 +Captain America,Marvel,1,2,10,Flight,Wooden Stake,0 +Superman,DC Comics,9,8,6,Super Strength,Kryptonite,0 +Superman,Marvel,9,9,7,Flight,Silver,0 +Superman,DC Comics,9,4,10,Super Strength,Silver,1 +Superman,Marvel,5,8,1,Invisibility,Magic,1 +Spider-Man,DC Comics,9,9,6,Invisibility,Silver,1 +Captain America,Marvel,4,10,7,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,2,10,6,Telekinesis,Magic,0 +Spider-Man,Marvel,6,5,4,Super Strength,Silver,0 +Batman,Marvel,4,7,1,Flight,Magic,0 +Spider-Man,DC Comics,6,10,9,Flight,Silver,0 +Flash,DC Comics,3,4,4,Flight,Wooden Stake,0 +Wonder Woman,Marvel,6,1,7,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,2,3,7,Telekinesis,Kryptonite,0 +Wonder Woman,DC Comics,2,5,2,Flight,Wooden Stake,0 +Superman,Marvel,9,3,1,Telekinesis,Wooden Stake,0 +Batman,DC Comics,7,7,8,Super Strength,Wooden Stake,1 +Spider-Man,Marvel,3,9,8,Invisibility,Silver,0 +Spider-Man,DC Comics,1,6,7,Flight,Silver,0 +Flash,Marvel,8,10,8,Invisibility,Magic,1 +Captain America,DC Comics,6,1,3,Super Strength,Silver,0 +Spider-Man,Marvel,7,7,2,Super Strength,Wooden Stake,0 +Flash,Marvel,9,3,7,Flight,Silver,0 +Batman,DC Comics,5,5,8,Super Strength,Kryptonite,0 +Superman,DC Comics,1,10,1,Invisibility,Magic,0 +Captain America,Marvel,10,4,10,Flight,Magic,1 +Flash,Marvel,7,10,9,Telekinesis,Silver,1 +Spider-Man,DC Comics,5,5,4,Flight,Wooden Stake,0 +Captain America,DC Comics,3,5,4,Invisibility,Magic,0 +Thor,DC Comics,9,6,3,Flight,Kryptonite,0 +Captain America,DC Comics,1,10,6,Flight,Kryptonite,0 +Wonder Woman,DC Comics,1,10,1,Invisibility,Magic,0 +Superman,DC Comics,1,6,6,Flight,Wooden Stake,0 +Wonder Woman,Marvel,3,8,2,Flight,Wooden Stake,0 +Thor,DC Comics,6,8,9,Invisibility,Silver,1 +Wonder Woman,DC Comics,10,9,2,Super Strength,Silver,0 +Thor,DC Comics,3,8,7,Invisibility,Magic,0 +Captain America,DC Comics,8,2,1,Flight,Silver,0 +Batman,Marvel,10,10,7,Telekinesis,Silver,1 +Superman,Marvel,2,1,5,Telekinesis,Silver,0 +Batman,Marvel,9,10,8,Invisibility,Kryptonite,1 +Superman,Marvel,3,2,4,Telekinesis,Silver,0 +Flash,DC Comics,5,2,10,Flight,Magic,0 +Superman,Marvel,10,3,7,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,8,10,6,Invisibility,Silver,0 +Wonder Woman,DC Comics,2,7,5,Flight,Wooden Stake,0 +Batman,Marvel,6,2,4,Super Strength,Silver,1 +Iron Man,Marvel,5,1,7,Flight,Magic,0 +Flash,DC Comics,10,6,5,Invisibility,Kryptonite,1 +Thor,Marvel,9,9,5,Super Strength,Magic,0 +Wonder Woman,Marvel,5,3,1,Super Strength,Kryptonite,0 +Flash,DC Comics,2,6,2,Telekinesis,Silver,0 +Wonder Woman,DC Comics,5,3,5,Flight,Silver,0 +Wonder Woman,DC Comics,4,1,3,Invisibility,Kryptonite,0 +Captain America,DC Comics,7,5,2,Telekinesis,Magic,0 +Batman,DC Comics,6,10,4,Telekinesis,Magic,0 +Batman,Marvel,2,4,4,Flight,Kryptonite,0 +Wonder Woman,DC Comics,5,7,4,Flight,Silver,1 +Captain America,DC Comics,7,6,4,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,7,10,3,Telekinesis,Silver,0 +Thor,Marvel,5,7,7,Invisibility,Kryptonite,0 +Captain America,DC Comics,9,5,9,Telekinesis,Silver,1 +Wonder Woman,DC Comics,4,4,5,Telekinesis,Kryptonite,0 +Superman,Marvel,3,7,4,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,4,7,2,Flight,Silver,0 +Superman,DC Comics,5,6,2,Telekinesis,Magic,0 +Iron Man,DC Comics,6,8,5,Telekinesis,Kryptonite,0 +Captain America,Marvel,3,4,7,Telekinesis,Magic,0 +Superman,Marvel,2,10,10,Super Strength,Kryptonite,0 +Thor,DC Comics,4,5,10,Flight,Magic,1 +Flash,DC Comics,5,4,9,Super Strength,Magic,1 +Superman,DC Comics,4,1,7,Flight,Kryptonite,0 +Batman,Marvel,3,8,5,Invisibility,Kryptonite,0 +Flash,Marvel,8,1,10,Super Strength,Magic,0 +Flash,Marvel,10,5,10,Invisibility,Magic,1 +Iron Man,Marvel,4,6,10,Telekinesis,Magic,0 +Iron Man,Marvel,2,6,6,Invisibility,Silver,1 +Wonder Woman,Marvel,2,5,3,Invisibility,Silver,0 +Thor,DC Comics,1,3,5,Invisibility,Wooden Stake,0 +Iron Man,Marvel,4,5,8,Invisibility,Silver,0 +Iron Man,DC Comics,10,8,1,Flight,Silver,1 +Wonder Woman,Marvel,9,2,1,Super Strength,Kryptonite,0 +Thor,DC Comics,7,6,7,Flight,Wooden Stake,1 +Superman,Marvel,10,9,5,Flight,Wooden Stake,1 +Captain America,DC Comics,7,8,5,Flight,Silver,0 +Superman,DC Comics,7,8,1,Invisibility,Kryptonite,0 +Batman,DC Comics,8,8,9,Flight,Kryptonite,0 +Batman,Marvel,1,7,1,Super Strength,Wooden Stake,0 +Iron Man,Marvel,10,8,5,Flight,Kryptonite,1 +Flash,Marvel,10,6,10,Telekinesis,Magic,1 +Batman,DC Comics,8,2,9,Invisibility,Silver,1 +Captain America,DC Comics,4,2,4,Telekinesis,Magic,0 +Iron Man,DC Comics,4,8,8,Super Strength,Wooden Stake,0 +Wonder Woman,Marvel,4,1,6,Super Strength,Wooden Stake,1 +Batman,Marvel,6,6,3,Super Strength,Kryptonite,0 +Flash,DC Comics,7,6,4,Super Strength,Kryptonite,0 +Wonder Woman,Marvel,6,4,2,Flight,Wooden Stake,0 +Spider-Man,Marvel,1,10,1,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,8,3,8,Super Strength,Magic,1 +Spider-Man,Marvel,10,3,1,Telekinesis,Magic,1 +Wonder Woman,DC Comics,7,1,1,Super Strength,Kryptonite,0 +Spider-Man,Marvel,6,3,4,Invisibility,Magic,1 +Superman,Marvel,6,4,10,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,5,5,10,Telekinesis,Kryptonite,0 +Iron Man,DC Comics,6,3,6,Telekinesis,Silver,0 +Thor,Marvel,9,6,9,Flight,Kryptonite,0 +Superman,Marvel,10,5,1,Super Strength,Magic,1 +Flash,Marvel,9,3,7,Flight,Wooden Stake,0 +Thor,Marvel,10,6,10,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,8,6,5,Flight,Magic,0 +Flash,DC Comics,10,8,8,Flight,Wooden Stake,0 +Iron Man,DC Comics,9,2,7,Flight,Kryptonite,0 +Captain America,Marvel,10,1,4,Super Strength,Wooden Stake,1 +Flash,Marvel,8,4,4,Telekinesis,Magic,1 +Superman,DC Comics,8,7,6,Telekinesis,Wooden Stake,1 +Thor,Marvel,1,10,6,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,10,3,9,Flight,Kryptonite,1 +Iron Man,DC Comics,5,3,5,Flight,Magic,0 +Spider-Man,DC Comics,4,5,8,Invisibility,Magic,0 +Flash,DC Comics,2,5,5,Invisibility,Magic,0 +Thor,DC Comics,8,10,2,Invisibility,Silver,0 +Wonder Woman,DC Comics,3,3,6,Super Strength,Silver,0 +Superman,DC Comics,4,9,9,Telekinesis,Kryptonite,0 +Batman,Marvel,7,4,3,Invisibility,Silver,1 +Wonder Woman,DC Comics,10,3,1,Telekinesis,Silver,0 +Flash,DC Comics,9,2,1,Telekinesis,Wooden Stake,0 +Flash,Marvel,2,10,3,Telekinesis,Silver,0 +Wonder Woman,DC Comics,3,9,10,Super Strength,Wooden Stake,1 +Batman,Marvel,4,4,5,Super Strength,Magic,1 +Flash,DC Comics,10,3,3,Super Strength,Wooden Stake,1 +Flash,Marvel,1,7,9,Super Strength,Wooden Stake,1 +Iron Man,Marvel,7,8,8,Invisibility,Magic,1 +Captain America,Marvel,2,2,3,Flight,Magic,0 +Flash,DC Comics,5,7,9,Flight,Kryptonite,0 +Spider-Man,Marvel,1,5,6,Flight,Kryptonite,0 +Iron Man,DC Comics,3,5,7,Invisibility,Kryptonite,0 +Captain America,DC Comics,2,3,4,Flight,Kryptonite,0 +Spider-Man,DC Comics,1,5,4,Invisibility,Wooden Stake,0 +Thor,DC Comics,7,2,2,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,5,4,5,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,1,6,8,Flight,Silver,0 +Batman,DC Comics,6,1,7,Telekinesis,Kryptonite,0 +Captain America,Marvel,5,10,7,Flight,Silver,0 +Spider-Man,DC Comics,3,4,6,Flight,Magic,0 +Flash,DC Comics,7,6,3,Super Strength,Wooden Stake,0 +Iron Man,Marvel,10,9,5,Invisibility,Wooden Stake,1 +Spider-Man,DC Comics,9,2,1,Telekinesis,Silver,0 +Iron Man,Marvel,9,7,7,Super Strength,Kryptonite,0 +Wonder Woman,Marvel,9,6,9,Telekinesis,Wooden Stake,1 +Batman,DC Comics,2,2,1,Telekinesis,Silver,0 +Flash,DC Comics,3,8,2,Invisibility,Magic,1 +Batman,Marvel,7,7,3,Flight,Magic,1 +Spider-Man,DC Comics,5,5,3,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,2,5,8,Invisibility,Kryptonite,0 +Iron Man,Marvel,3,7,7,Super Strength,Silver,1 +Iron Man,DC Comics,10,9,6,Invisibility,Wooden Stake,1 +Captain America,Marvel,6,9,10,Flight,Magic,1 +Wonder Woman,DC Comics,7,9,10,Telekinesis,Kryptonite,0 +Captain America,DC Comics,9,6,4,Invisibility,Silver,0 +Captain America,Marvel,1,10,9,Telekinesis,Wooden Stake,0 +Spider-Man,Marvel,7,6,1,Invisibility,Silver,0 +Superman,DC Comics,8,3,2,Telekinesis,Kryptonite,0 +Superman,DC Comics,3,1,4,Invisibility,Kryptonite,0 +Superman,DC Comics,4,7,3,Super Strength,Magic,1 +Superman,Marvel,10,4,1,Telekinesis,Kryptonite,0 +Captain America,DC Comics,6,1,5,Invisibility,Wooden Stake,0 +Spider-Man,Marvel,10,8,7,Invisibility,Silver,1 +Superman,Marvel,7,6,2,Super Strength,Kryptonite,0 +Flash,Marvel,4,6,5,Super Strength,Kryptonite,0 +Batman,DC Comics,8,2,6,Super Strength,Wooden Stake,1 +Thor,Marvel,5,1,7,Telekinesis,Silver,0 +Batman,DC Comics,1,2,1,Telekinesis,Silver,0 +Spider-Man,Marvel,4,4,7,Super Strength,Magic,1 +Spider-Man,DC Comics,3,2,4,Flight,Magic,0 +Thor,DC Comics,9,1,8,Flight,Silver,0 +Iron Man,Marvel,8,7,4,Invisibility,Wooden Stake,1 +Iron Man,DC Comics,1,8,6,Flight,Wooden Stake,0 +Flash,Marvel,6,6,9,Invisibility,Magic,0 +Iron Man,Marvel,9,4,5,Telekinesis,Kryptonite,0 +Captain America,Marvel,7,6,4,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,4,3,8,Flight,Kryptonite,0 +Wonder Woman,Marvel,1,8,9,Telekinesis,Wooden Stake,0 +Captain America,Marvel,2,10,4,Super Strength,Silver,1 +Captain America,Marvel,5,2,3,Super Strength,Magic,1 +Flash,DC Comics,5,5,8,Flight,Kryptonite,0 +Iron Man,Marvel,8,1,5,Flight,Kryptonite,0 +Iron Man,Marvel,6,6,2,Invisibility,Silver,0 +Flash,DC Comics,8,2,10,Telekinesis,Wooden Stake,1 +Thor,DC Comics,2,4,9,Invisibility,Kryptonite,0 +Superman,Marvel,3,6,3,Invisibility,Wooden Stake,0 +Flash,Marvel,6,10,2,Super Strength,Silver,0 +Thor,Marvel,10,8,1,Super Strength,Magic,0 +Captain America,DC Comics,3,8,8,Super Strength,Kryptonite,0 +Thor,Marvel,6,6,3,Super Strength,Wooden Stake,0 +Captain America,DC Comics,6,4,7,Invisibility,Kryptonite,0 +Spider-Man,Marvel,2,8,1,Super Strength,Wooden Stake,0 +Captain America,Marvel,7,8,1,Telekinesis,Wooden Stake,1 +Captain America,DC Comics,2,10,9,Super Strength,Wooden Stake,1 +Thor,Marvel,6,1,8,Super Strength,Silver,1 +Superman,Marvel,1,4,3,Super Strength,Magic,0 +Spider-Man,Marvel,3,4,6,Flight,Kryptonite,0 +Batman,DC Comics,2,7,3,Telekinesis,Magic,0 +Batman,Marvel,7,7,4,Telekinesis,Wooden Stake,1 +Superman,Marvel,4,8,1,Invisibility,Wooden Stake,0 +Batman,DC Comics,8,5,5,Invisibility,Magic,1 +Spider-Man,DC Comics,6,7,1,Super Strength,Magic,0 +Iron Man,Marvel,10,8,1,Flight,Kryptonite,0 +Spider-Man,Marvel,4,9,10,Invisibility,Wooden Stake,0 +Thor,DC Comics,5,3,7,Invisibility,Magic,0 +Flash,Marvel,9,3,6,Super Strength,Silver,1 +Wonder Woman,Marvel,7,4,2,Super Strength,Wooden Stake,0 +Captain America,DC Comics,10,5,2,Invisibility,Wooden Stake,1 +Captain America,Marvel,9,10,7,Invisibility,Kryptonite,0 +Flash,Marvel,7,1,1,Telekinesis,Silver,0 +Thor,DC Comics,1,7,2,Flight,Kryptonite,0 +Thor,Marvel,8,9,8,Telekinesis,Silver,0 +Wonder Woman,Marvel,4,8,6,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,3,5,2,Telekinesis,Silver,0 +Captain America,DC Comics,7,4,7,Telekinesis,Silver,1 +Wonder Woman,Marvel,3,7,4,Invisibility,Silver,0 +Wonder Woman,DC Comics,8,5,2,Super Strength,Magic,1 +Wonder Woman,DC Comics,6,7,6,Invisibility,Wooden Stake,0 +Flash,Marvel,5,1,9,Super Strength,Silver,1 +Superman,DC Comics,4,1,9,Invisibility,Magic,1 +Iron Man,Marvel,8,10,8,Invisibility,Magic,1 +Wonder Woman,Marvel,8,3,3,Invisibility,Kryptonite,0 +Iron Man,Marvel,1,2,3,Flight,Wooden Stake,0 +Iron Man,DC Comics,9,2,2,Super Strength,Wooden Stake,1 +Thor,Marvel,5,7,5,Flight,Kryptonite,0 +Wonder Woman,Marvel,4,10,4,Invisibility,Wooden Stake,0 +Captain America,Marvel,6,2,7,Telekinesis,Kryptonite,0 +Superman,DC Comics,6,4,4,Flight,Magic,0 +Captain America,DC Comics,2,2,9,Super Strength,Magic,0 +Wonder Woman,Marvel,8,6,2,Invisibility,Silver,0 +Captain America,Marvel,7,8,6,Flight,Kryptonite,0 +Wonder Woman,Marvel,1,10,7,Telekinesis,Magic,0 +Superman,Marvel,5,4,4,Flight,Magic,0 +Spider-Man,DC Comics,6,5,6,Super Strength,Kryptonite,0 +Superman,DC Comics,4,4,7,Flight,Magic,0 +Flash,DC Comics,2,3,4,Telekinesis,Wooden Stake,0 +Spider-Man,DC Comics,4,5,8,Telekinesis,Magic,0 +Batman,DC Comics,1,9,9,Super Strength,Kryptonite,0 +Spider-Man,DC Comics,7,8,1,Telekinesis,Wooden Stake,1 +Iron Man,DC Comics,2,8,7,Invisibility,Wooden Stake,0 +Flash,Marvel,2,8,9,Telekinesis,Magic,1 +Iron Man,Marvel,9,8,10,Invisibility,Silver,1 +Flash,Marvel,5,7,5,Flight,Wooden Stake,0 +Superman,Marvel,2,8,2,Invisibility,Kryptonite,0 +Iron Man,Marvel,9,8,10,Invisibility,Silver,1 +Iron Man,Marvel,9,8,6,Flight,Silver,1 +Batman,DC Comics,1,10,7,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,3,7,2,Invisibility,Magic,0 +Thor,DC Comics,4,1,2,Telekinesis,Silver,0 +Thor,Marvel,7,4,10,Flight,Magic,0 +Thor,DC Comics,10,4,10,Super Strength,Wooden Stake,1 +Spider-Man,DC Comics,4,5,1,Telekinesis,Kryptonite,0 +Superman,Marvel,2,10,4,Telekinesis,Silver,0 +Superman,Marvel,7,6,7,Super Strength,Kryptonite,1 +Captain America,Marvel,6,4,9,Super Strength,Magic,1 +Batman,Marvel,3,2,3,Flight,Magic,0 +Thor,Marvel,6,6,7,Telekinesis,Kryptonite,0 +Thor,DC Comics,6,8,7,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,5,8,7,Flight,Wooden Stake,0 +Thor,DC Comics,4,7,2,Telekinesis,Silver,0 +Iron Man,DC Comics,10,6,6,Invisibility,Silver,1 +Iron Man,DC Comics,1,2,2,Invisibility,Wooden Stake,0 +Captain America,Marvel,10,7,6,Invisibility,Wooden Stake,1 +Spider-Man,Marvel,6,5,10,Telekinesis,Kryptonite,0 +Iron Man,Marvel,2,6,3,Invisibility,Magic,0 +Iron Man,Marvel,3,10,2,Invisibility,Magic,0 +Superman,Marvel,8,8,6,Flight,Silver,1 +Captain America,Marvel,10,8,2,Flight,Wooden Stake,1 +Iron Man,DC Comics,6,3,5,Super Strength,Kryptonite,0 +Batman,Marvel,3,7,2,Super Strength,Silver,0 +Spider-Man,DC Comics,7,1,3,Super Strength,Kryptonite,0 +Flash,DC Comics,4,1,3,Super Strength,Wooden Stake,0 +Batman,Marvel,9,7,6,Flight,Wooden Stake,1 +Thor,Marvel,5,10,6,Flight,Wooden Stake,0 +Spider-Man,Marvel,3,9,10,Flight,Magic,0 +Thor,Marvel,2,7,3,Invisibility,Wooden Stake,0 +Superman,Marvel,2,10,3,Invisibility,Silver,1 +Wonder Woman,Marvel,3,5,1,Super Strength,Magic,0 +Wonder Woman,DC Comics,2,8,7,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,4,2,8,Telekinesis,Silver,0 +Iron Man,DC Comics,2,9,2,Flight,Silver,0 +Captain America,DC Comics,10,6,4,Super Strength,Kryptonite,0 +Batman,DC Comics,9,9,10,Super Strength,Magic,1 +Thor,DC Comics,2,2,7,Telekinesis,Silver,0 +Iron Man,Marvel,9,3,8,Invisibility,Silver,1 +Wonder Woman,Marvel,6,8,1,Super Strength,Silver,1 +Batman,Marvel,1,1,4,Invisibility,Magic,0 +Batman,DC Comics,4,10,6,Invisibility,Magic,1 +Superman,DC Comics,1,7,3,Telekinesis,Magic,0 +Superman,DC Comics,6,7,5,Super Strength,Silver,0 +Wonder Woman,Marvel,4,1,10,Invisibility,Wooden Stake,0 +Thor,Marvel,3,9,9,Invisibility,Kryptonite,1 +Wonder Woman,Marvel,3,8,3,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,9,4,5,Telekinesis,Magic,1 +Iron Man,DC Comics,6,10,8,Invisibility,Silver,1 +Captain America,DC Comics,9,5,6,Telekinesis,Silver,1 +Wonder Woman,Marvel,5,2,4,Invisibility,Wooden Stake,0 +Thor,DC Comics,2,9,8,Super Strength,Wooden Stake,1 +Batman,Marvel,8,6,3,Flight,Kryptonite,0 +Batman,Marvel,5,3,3,Telekinesis,Silver,0 +Flash,Marvel,2,7,4,Flight,Wooden Stake,0 +Spider-Man,Marvel,4,9,9,Invisibility,Kryptonite,1 +Wonder Woman,Marvel,9,3,5,Invisibility,Magic,0 +Flash,Marvel,4,2,8,Invisibility,Wooden Stake,0 +Flash,Marvel,4,7,6,Flight,Magic,0 +Iron Man,DC Comics,2,7,3,Invisibility,Kryptonite,0 +Spider-Man,Marvel,6,4,8,Telekinesis,Magic,0 +Superman,DC Comics,2,9,9,Super Strength,Silver,0 +Captain America,Marvel,7,8,8,Super Strength,Silver,1 +Thor,Marvel,3,1,4,Telekinesis,Magic,0 +Wonder Woman,Marvel,3,1,6,Super Strength,Silver,0 +Batman,DC Comics,5,5,1,Flight,Kryptonite,0 +Iron Man,Marvel,3,6,4,Invisibility,Silver,1 +Batman,Marvel,2,3,8,Invisibility,Magic,1 +Wonder Woman,DC Comics,10,9,1,Invisibility,Magic,0 +Superman,DC Comics,9,10,3,Flight,Magic,0 +Spider-Man,DC Comics,2,6,1,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,2,4,9,Flight,Magic,1 +Spider-Man,Marvel,8,7,2,Telekinesis,Kryptonite,0 +Thor,Marvel,9,8,9,Flight,Silver,0 +Iron Man,DC Comics,7,9,4,Super Strength,Silver,1 +Superman,Marvel,3,6,2,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,9,6,4,Telekinesis,Wooden Stake,0 +Thor,DC Comics,3,8,10,Telekinesis,Kryptonite,0 +Superman,DC Comics,5,5,6,Flight,Magic,0 +Flash,Marvel,9,3,7,Telekinesis,Wooden Stake,0 +Superman,DC Comics,3,3,3,Flight,Silver,0 +Spider-Man,Marvel,7,6,3,Flight,Wooden Stake,0 +Spider-Man,Marvel,1,2,10,Telekinesis,Wooden Stake,0 +Spider-Man,Marvel,4,6,8,Invisibility,Magic,1 +Batman,DC Comics,4,6,5,Invisibility,Wooden Stake,1 +Flash,Marvel,7,8,4,Telekinesis,Kryptonite,0 +Captain America,DC Comics,8,7,7,Invisibility,Silver,1 +Wonder Woman,Marvel,1,8,7,Super Strength,Magic,1 +Spider-Man,Marvel,5,9,9,Super Strength,Silver,1 +Captain America,Marvel,7,6,9,Flight,Kryptonite,0 +Captain America,DC Comics,4,3,5,Invisibility,Kryptonite,0 +Iron Man,DC Comics,4,10,8,Super Strength,Wooden Stake,1 +Thor,DC Comics,4,3,10,Telekinesis,Wooden Stake,0 +Batman,DC Comics,6,1,1,Invisibility,Wooden Stake,0 +Captain America,Marvel,7,5,9,Super Strength,Silver,1 +Wonder Woman,Marvel,2,4,8,Super Strength,Kryptonite,0 +Batman,DC Comics,5,9,6,Telekinesis,Magic,1 +Iron Man,DC Comics,4,9,3,Flight,Wooden Stake,0 +Spider-Man,DC Comics,3,5,3,Telekinesis,Silver,0 +Superman,DC Comics,7,10,8,Flight,Wooden Stake,1 +Captain America,Marvel,6,4,5,Super Strength,Kryptonite,0 +Thor,DC Comics,7,7,10,Flight,Magic,1 +Superman,DC Comics,5,6,7,Super Strength,Kryptonite,1 +Iron Man,Marvel,6,4,5,Super Strength,Silver,0 +Batman,DC Comics,5,10,8,Invisibility,Wooden Stake,1 +Wonder Woman,Marvel,7,2,10,Flight,Kryptonite,0 +Flash,DC Comics,2,1,10,Flight,Silver,0 +Spider-Man,Marvel,5,4,4,Flight,Wooden Stake,0 +Batman,DC Comics,6,4,2,Telekinesis,Magic,0 +Thor,DC Comics,6,1,3,Invisibility,Kryptonite,0 +Captain America,DC Comics,5,6,8,Invisibility,Wooden Stake,0 +Thor,DC Comics,10,4,7,Invisibility,Wooden Stake,1 +Batman,DC Comics,7,1,2,Telekinesis,Wooden Stake,0 +Batman,Marvel,10,1,6,Flight,Wooden Stake,0 +Superman,DC Comics,8,1,9,Flight,Kryptonite,0 +Thor,Marvel,7,8,4,Flight,Wooden Stake,0 +Thor,Marvel,5,10,9,Invisibility,Silver,1 +Thor,Marvel,1,8,2,Invisibility,Kryptonite,0 +Spider-Man,Marvel,5,2,2,Super Strength,Wooden Stake,0 +Wonder Woman,DC Comics,10,7,9,Telekinesis,Kryptonite,1 +Batman,DC Comics,2,8,7,Telekinesis,Silver,1 +Iron Man,DC Comics,5,8,7,Invisibility,Silver,0 +Spider-Man,DC Comics,5,10,1,Super Strength,Kryptonite,0 +Spider-Man,Marvel,2,7,6,Flight,Wooden Stake,1 +Spider-Man,Marvel,5,5,7,Invisibility,Wooden Stake,0 +Superman,Marvel,4,1,6,Telekinesis,Silver,0 +Flash,DC Comics,1,9,6,Telekinesis,Wooden Stake,0 +Wonder Woman,DC Comics,3,7,2,Telekinesis,Silver,0 +Wonder Woman,DC Comics,1,2,6,Flight,Wooden Stake,0 +Iron Man,DC Comics,5,6,4,Telekinesis,Silver,0 +Flash,Marvel,4,2,9,Flight,Magic,0 +Thor,DC Comics,7,1,1,Flight,Wooden Stake,0 +Superman,DC Comics,5,7,8,Flight,Wooden Stake,1 +Batman,Marvel,10,2,5,Invisibility,Wooden Stake,1 +Flash,Marvel,4,2,1,Flight,Kryptonite,0 +Captain America,DC Comics,2,5,4,Super Strength,Wooden Stake,1 +Superman,DC Comics,4,5,1,Telekinesis,Kryptonite,0 +Captain America,Marvel,2,7,6,Invisibility,Kryptonite,0 +Batman,DC Comics,8,1,2,Telekinesis,Silver,0 +Iron Man,Marvel,3,8,5,Flight,Kryptonite,0 +Wonder Woman,Marvel,9,3,7,Invisibility,Kryptonite,0 +Captain America,DC Comics,4,4,2,Super Strength,Magic,0 +Spider-Man,Marvel,6,9,6,Flight,Wooden Stake,1 +Superman,DC Comics,10,4,6,Telekinesis,Kryptonite,0 +Flash,DC Comics,5,10,5,Super Strength,Wooden Stake,1 +Flash,DC Comics,10,5,5,Flight,Kryptonite,0 +Captain America,DC Comics,1,7,3,Super Strength,Silver,0 +Batman,Marvel,9,4,10,Flight,Magic,0 +Wonder Woman,DC Comics,1,1,10,Invisibility,Kryptonite,0 +Spider-Man,DC Comics,8,9,2,Flight,Wooden Stake,0 +Flash,Marvel,9,4,7,Invisibility,Silver,1 +Captain America,DC Comics,9,9,1,Flight,Wooden Stake,0 +Wonder Woman,DC Comics,1,6,6,Flight,Silver,0 +Batman,DC Comics,2,1,6,Telekinesis,Magic,0 +Iron Man,DC Comics,1,3,3,Super Strength,Silver,0 +Batman,Marvel,10,2,2,Super Strength,Wooden Stake,1 +Iron Man,Marvel,2,9,2,Super Strength,Wooden Stake,0 +Flash,DC Comics,10,1,9,Flight,Kryptonite,0 +Wonder Woman,Marvel,8,9,5,Flight,Silver,0 +Wonder Woman,Marvel,5,9,7,Flight,Wooden Stake,1 +Spider-Man,Marvel,7,8,5,Invisibility,Kryptonite,0 +Batman,Marvel,2,8,7,Invisibility,Magic,0 +Thor,DC Comics,8,1,4,Telekinesis,Wooden Stake,0 +Flash,Marvel,6,8,8,Flight,Kryptonite,0 +Superman,DC Comics,8,10,10,Super Strength,Wooden Stake,1 +Thor,DC Comics,1,3,10,Super Strength,Silver,0 +Flash,Marvel,1,7,7,Telekinesis,Kryptonite,0 +Thor,DC Comics,7,1,10,Super Strength,Silver,0 +Thor,Marvel,8,1,5,Telekinesis,Magic,0 +Superman,DC Comics,3,10,6,Flight,Silver,0 +Thor,DC Comics,5,5,5,Super Strength,Kryptonite,0 +Iron Man,Marvel,1,5,7,Flight,Wooden Stake,0 +Batman,DC Comics,7,8,2,Invisibility,Kryptonite,0 +Wonder Woman,Marvel,5,7,5,Super Strength,Silver,1 +Spider-Man,DC Comics,8,8,10,Invisibility,Silver,1 +Thor,DC Comics,8,6,3,Super Strength,Wooden Stake,1 +Wonder Woman,Marvel,9,6,9,Flight,Magic,0 +Thor,Marvel,7,2,6,Telekinesis,Kryptonite,0 +Flash,Marvel,1,6,10,Flight,Wooden Stake,0 +Spider-Man,DC Comics,3,5,3,Flight,Wooden Stake,0 +Flash,Marvel,8,3,7,Flight,Wooden Stake,1 +Spider-Man,Marvel,3,6,4,Super Strength,Kryptonite,0 +Thor,Marvel,8,8,3,Telekinesis,Kryptonite,0 +Iron Man,Marvel,1,9,8,Invisibility,Kryptonite,0 +Wonder Woman,DC Comics,5,1,4,Flight,Magic,0 +Spider-Man,DC Comics,4,3,1,Super Strength,Wooden Stake,0 +Batman,DC Comics,5,3,6,Invisibility,Silver,1 +Wonder Woman,DC Comics,8,8,10,Flight,Silver,1 +Batman,DC Comics,10,1,1,Invisibility,Wooden Stake,0 +Wonder Woman,DC Comics,4,5,5,Flight,Silver,0 +Iron Man,Marvel,4,3,7,Invisibility,Magic,1 +Flash,DC Comics,3,2,6,Invisibility,Magic,0 +Superman,Marvel,7,8,2,Telekinesis,Kryptonite,0 +Flash,Marvel,3,3,4,Telekinesis,Kryptonite,0 +Captain America,Marvel,3,7,2,Flight,Kryptonite,0 +Iron Man,Marvel,10,1,1,Super Strength,Kryptonite,0 +Thor,DC Comics,5,6,3,Telekinesis,Kryptonite,0 +Captain America,DC Comics,5,3,3,Invisibility,Silver,0 +Thor,DC Comics,6,8,7,Telekinesis,Silver,1 +Batman,Marvel,8,6,1,Telekinesis,Kryptonite,0 +Spider-Man,DC Comics,10,2,9,Flight,Magic,1 +Wonder Woman,DC Comics,6,6,6,Telekinesis,Silver,0 +Thor,DC Comics,1,7,4,Telekinesis,Magic,0 +Batman,DC Comics,8,5,3,Invisibility,Magic,0 +Iron Man,DC Comics,8,3,3,Telekinesis,Wooden Stake,1 +Thor,DC Comics,9,4,2,Invisibility,Wooden Stake,0 +Flash,Marvel,9,4,2,Telekinesis,Kryptonite,0 +Batman,Marvel,2,6,10,Telekinesis,Magic,0 +Spider-Man,DC Comics,2,10,5,Super Strength,Silver,0 +Wonder Woman,Marvel,3,1,9,Telekinesis,Wooden Stake,0 +Thor,Marvel,1,4,2,Invisibility,Wooden Stake,0 +Superman,DC Comics,4,10,2,Invisibility,Magic,0 +Batman,Marvel,4,4,6,Flight,Wooden Stake,0 +Thor,DC Comics,9,10,10,Flight,Wooden Stake,0 +Spider-Man,Marvel,9,1,2,Super Strength,Silver,0 +Wonder Woman,DC Comics,9,9,4,Invisibility,Magic,1 +Thor,Marvel,10,4,6,Invisibility,Wooden Stake,1 +Thor,Marvel,7,7,5,Invisibility,Magic,1 +Wonder Woman,Marvel,2,3,1,Super Strength,Wooden Stake,0 +Superman,Marvel,10,10,6,Invisibility,Silver,1 +Batman,DC Comics,5,3,1,Flight,Magic,0 +Captain America,Marvel,4,8,3,Super Strength,Wooden Stake,0 +Flash,DC Comics,8,8,10,Flight,Silver,1 +Wonder Woman,DC Comics,2,1,5,Flight,Wooden Stake,0 +Thor,Marvel,6,10,10,Super Strength,Magic,1 +Captain America,Marvel,5,2,5,Telekinesis,Wooden Stake,0 +Iron Man,DC Comics,2,8,10,Telekinesis,Magic,0 +Thor,Marvel,10,1,6,Flight,Magic,0 +Captain America,DC Comics,1,8,10,Telekinesis,Wooden Stake,0 +Iron Man,Marvel,8,8,8,Invisibility,Silver,1 +Superman,DC Comics,2,2,5,Super Strength,Kryptonite,0 +Batman,Marvel,7,4,1,Flight,Silver,0 +Thor,Marvel,9,6,5,Invisibility,Silver,0 +Batman,DC Comics,9,9,3,Telekinesis,Wooden Stake,1 +Iron Man,DC Comics,8,8,4,Invisibility,Silver,0 +Batman,DC Comics,10,8,8,Telekinesis,Silver,1 +Batman,Marvel,9,7,7,Flight,Kryptonite,0 +Wonder Woman,Marvel,2,9,5,Invisibility,Silver,0 +Spider-Man,Marvel,6,2,2,Super Strength,Kryptonite,0 +Iron Man,Marvel,4,3,6,Flight,Wooden Stake,0 +Batman,DC Comics,4,10,6,Invisibility,Kryptonite,0 +Flash,DC Comics,5,8,10,Invisibility,Magic,0 +Captain America,Marvel,3,6,10,Telekinesis,Magic,1 +Iron Man,Marvel,1,10,6,Flight,Kryptonite,0 +Spider-Man,Marvel,8,9,9,Flight,Magic,1 +Thor,DC Comics,5,10,8,Flight,Wooden Stake,0 +Superman,DC Comics,3,4,8,Flight,Magic,0 +Batman,Marvel,10,8,1,Telekinesis,Kryptonite,0 +Captain America,DC Comics,7,10,5,Super Strength,Wooden Stake,1 +Spider-Man,Marvel,7,3,7,Flight,Magic,0 +Iron Man,Marvel,1,3,6,Telekinesis,Wooden Stake,0 +Superman,DC Comics,9,8,5,Super Strength,Kryptonite,0 +Superman,DC Comics,2,5,8,Super Strength,Magic,1 +Flash,DC Comics,5,3,3,Telekinesis,Wooden Stake,0 +Batman,DC Comics,5,10,6,Flight,Wooden Stake,1 +Spider-Man,Marvel,8,1,5,Super Strength,Magic,1 diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___13_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___13_0.png new file mode 100644 index 000000000..40ed9aabe Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___13_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___14_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___14_0.png new file mode 100644 index 000000000..7f309ae32 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___14_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___15_1.png b/Fictional Character Battle Outcome Prediction/Images/__results___15_1.png new file mode 100644 index 000000000..3d8a65826 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___15_1.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___15_3.png b/Fictional Character Battle Outcome Prediction/Images/__results___15_3.png new file mode 100644 index 000000000..24fb8fc98 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___15_3.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___15_5.png b/Fictional Character Battle Outcome Prediction/Images/__results___15_5.png new file mode 100644 index 000000000..3402234be Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___15_5.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___16_1.png b/Fictional Character Battle Outcome Prediction/Images/__results___16_1.png new file mode 100644 index 000000000..e2ce25aae Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___16_1.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___17_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___17_0.png new file mode 100644 index 000000000..99843535e Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___17_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___18_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___18_0.png new file mode 100644 index 000000000..0e2a87067 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___18_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___19_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___19_0.png new file mode 100644 index 000000000..a6a9ab3de Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___19_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___20_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___20_0.png new file mode 100644 index 000000000..97715ef4e Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___20_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___21_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___21_0.png new file mode 100644 index 000000000..2a3b2c423 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___21_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_0.png new file mode 100644 index 000000000..df754bf26 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_1.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_1.png new file mode 100644 index 000000000..df7196603 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_1.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_10.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_10.png new file mode 100644 index 000000000..0ee6834df Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_10.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_11.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_11.png new file mode 100644 index 000000000..27da1881f Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_11.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_2.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_2.png new file mode 100644 index 000000000..41df0d37f Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_2.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_3.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_3.png new file mode 100644 index 000000000..016994524 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_3.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_4.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_4.png new file mode 100644 index 000000000..3a330182e Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_4.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_5.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_5.png new file mode 100644 index 000000000..b5bae7bb7 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_5.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_6.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_6.png new file mode 100644 index 000000000..4be3ed1c0 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_6.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_8.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_8.png new file mode 100644 index 000000000..8feb9b782 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_8.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___25_9.png b/Fictional Character Battle Outcome Prediction/Images/__results___25_9.png new file mode 100644 index 000000000..b5a104bf8 Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___25_9.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___30_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___30_0.png new file mode 100644 index 000000000..4db2b5b0f Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___30_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Images/__results___31_0.png b/Fictional Character Battle Outcome Prediction/Images/__results___31_0.png new file mode 100644 index 000000000..244ee9ebc Binary files /dev/null and b/Fictional Character Battle Outcome Prediction/Images/__results___31_0.png differ diff --git a/Fictional Character Battle Outcome Prediction/Models/README.md b/Fictional Character Battle Outcome Prediction/Models/README.md new file mode 100644 index 000000000..6edcfa651 --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/Models/README.md @@ -0,0 +1,77 @@ +# Models Implemented in Fictional Character Battle Outcome Prediction Project + +This document provides details on the machine learning models implemented in the "Fictional Character Battle Outcome Prediction" project. + +## Models and Their Accuracies + +1. **Random Forest**: + - Accuracy: 75.27% + - A versatile ensemble learning method that operates by constructing multiple decision trees during training and outputs the mode of the classes for classification. + +2. **Support Vector Classifier (SVC)**: + - Accuracy: 77.40% + - A supervised learning model that analyzes data for classification by finding the hyperplane that best separates the classes. + +3. **Logistic Regression**: + - Accuracy: 76.33% + - A statistical model that in its basic form uses a logistic function to model a binary dependent variable. + +4. **Decision Tree**: + - Accuracy: 71.00% + - A decision support tool that uses a tree-like graph of decisions and their possible consequences. + +5. **K-Nearest Neighbors (KNN)**: + - Accuracy: 73.56% + - A simple, instance-based learning algorithm that assigns a class to a sample based on the majority class among its k-nearest neighbors. + +6. **Gradient Boosting**: + - Accuracy: 77.40% + - An ensemble technique that builds models sequentially, each new model correcting errors made by previous models. + +7. **AdaBoost**: + - Accuracy: 78.25% + - A boosting algorithm that combines the predictions of several base estimators to improve robustness over a single estimator. + +8. **CatBoost**: + - Accuracy: 76.12% + - A high-performance library for gradient boosting on decision trees, especially well-suited for categorical data. + +9. **Extra Trees**: + - Accuracy: 73.35% + - An ensemble learning method similar to Random Forest but with more randomness in the splitting of nodes. + +10. **XGBoost**: + - Accuracy: 72.71% + - An optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. + +11. **Bagging Classifier**: + - Accuracy: 73.99% + - An ensemble meta-estimator that fits base classifiers each on random subsets of the original dataset and then aggregates their predictions. + +12. **Stacking Classifier**: + - Accuracy: 75.27% + - An ensemble learning technique that combines multiple base classifiers via a meta-classifier. The base classifiers are trained on the training dataset, and the meta-classifier is trained on the outputs of the base classifiers. + +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_1.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_2.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_3.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_4.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_5.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_6.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_7.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_8.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_9.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_10.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___25_11.png?raw=true) + +## Conclusion +Among the models evaluated, **AdaBoost** achieved the highest accuracy of 78.25%. This model is the best performer due to its ability to adaptively adjust the weights of misclassified instances, leading to improved performance in the prediction task. AdaBoost’s strong performance across multiple metrics, including precision, recall, and F1 score, highlights its effectiveness in handling this classification problem. + +## Signature + +**Name:** Aditya D +**Github:** [https://www.github.com/adi271001](https://www.github.com/adi271001) +**LinkedIn:** [https://www.linkedin.com/in/aditya-d-23453a179/](https://www.linkedin.com/in/aditya-d-23453a179/) +**Topmate:** [https://topmate.io/aditya_d/](https://topmate.io/aditya_d/) +**Twitter:** [https://x.com/ADITYAD29257528](https://x.com/ADITYAD29257528) diff --git a/Fictional Character Battle Outcome Prediction/Models/fictional-character-battle-outcome.ipynb b/Fictional Character Battle Outcome Prediction/Models/fictional-character-battle-outcome.ipynb new file mode 100644 index 000000000..c0613be09 --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/Models/fictional-character-battle-outcome.ipynb @@ -0,0 +1 @@ +{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":8715864,"sourceType":"datasetVersion","datasetId":5229220}],"dockerImageVersionId":30746,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import QuantileTransformer, PowerTransformer, LabelEncoder\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier\nfrom sklearn.svm import SVC\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.metrics import accuracy_score, confusion_matrix, classification_report, ConfusionMatrixDisplay\nfrom scipy.stats import shapiro, ttest_ind, f_oneway","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:58.968142Z","iopub.execute_input":"2024-07-21T17:49:58.968553Z","iopub.status.idle":"2024-07-21T17:49:58.976760Z","shell.execute_reply.started":"2024-07-21T17:49:58.968518Z","shell.execute_reply":"2024-07-21T17:49:58.975448Z"},"trusted":true},"execution_count":48,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv(\"/kaggle/input/fictional-character-battle-outcome-prediction/fictional_character_battles_complex.csv\")","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.120875Z","iopub.execute_input":"2024-07-21T17:49:59.121391Z","iopub.status.idle":"2024-07-21T17:49:59.160231Z","shell.execute_reply.started":"2024-07-21T17:49:59.121341Z","shell.execute_reply":"2024-07-21T17:49:59.158646Z"},"trusted":true},"execution_count":49,"outputs":[]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.162269Z","iopub.execute_input":"2024-07-21T17:49:59.162629Z","iopub.status.idle":"2024-07-21T17:49:59.178881Z","shell.execute_reply.started":"2024-07-21T17:49:59.162599Z","shell.execute_reply":"2024-07-21T17:49:59.177499Z"},"trusted":true},"execution_count":50,"outputs":[{"execution_count":50,"output_type":"execute_result","data":{"text/plain":" Character Universe Strength Speed Intelligence SpecialAbilities \\\n0 Wonder Woman Marvel 7 8 3 Telekinesis \n1 Iron Man Marvel 4 7 9 Telekinesis \n2 Iron Man DC Comics 8 7 5 Telekinesis \n3 Spider-Man DC Comics 5 6 10 Telekinesis \n4 Flash Marvel 7 6 2 Invisibility \n\n Weaknesses BattleOutcome \n0 Kryptonite 0 \n1 Kryptonite 0 \n2 Magic 0 \n3 Kryptonite 0 \n4 Magic 0 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
CharacterUniverseStrengthSpeedIntelligenceSpecialAbilitiesWeaknessesBattleOutcome
0Wonder WomanMarvel783TelekinesisKryptonite0
1Iron ManMarvel479TelekinesisKryptonite0
2Iron ManDC Comics875TelekinesisMagic0
3Spider-ManDC Comics5610TelekinesisKryptonite0
4FlashMarvel762InvisibilityMagic0
\n
"},"metadata":{}}]},{"cell_type":"code","source":"df.isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.181341Z","iopub.execute_input":"2024-07-21T17:49:59.181778Z","iopub.status.idle":"2024-07-21T17:49:59.200241Z","shell.execute_reply.started":"2024-07-21T17:49:59.181746Z","shell.execute_reply":"2024-07-21T17:49:59.198686Z"},"trusted":true},"execution_count":51,"outputs":[{"execution_count":51,"output_type":"execute_result","data":{"text/plain":"Character 0\nUniverse 0\nStrength 0\nSpeed 0\nIntelligence 0\nSpecialAbilities 0\nWeaknesses 0\nBattleOutcome 0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"# Check for duplicates and remove them\nduplicates = df.duplicated()\nprint(\"\\nNumber of Duplicates:\", duplicates.sum())","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.203672Z","iopub.execute_input":"2024-07-21T17:49:59.204613Z","iopub.status.idle":"2024-07-21T17:49:59.222209Z","shell.execute_reply.started":"2024-07-21T17:49:59.204564Z","shell.execute_reply":"2024-07-21T17:49:59.219565Z"},"trusted":true},"execution_count":52,"outputs":[{"name":"stdout","text":"\nNumber of Duplicates: 6\n","output_type":"stream"}]},{"cell_type":"code","source":"df = df.drop_duplicates()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.225994Z","iopub.execute_input":"2024-07-21T17:49:59.226430Z","iopub.status.idle":"2024-07-21T17:49:59.239975Z","shell.execute_reply.started":"2024-07-21T17:49:59.226395Z","shell.execute_reply":"2024-07-21T17:49:59.238065Z"},"trusted":true},"execution_count":53,"outputs":[]},{"cell_type":"code","source":"# Basic info and statistics\nprint(\"\\nData Info:\")\ndf.info()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.241685Z","iopub.execute_input":"2024-07-21T17:49:59.242099Z","iopub.status.idle":"2024-07-21T17:49:59.275356Z","shell.execute_reply.started":"2024-07-21T17:49:59.242063Z","shell.execute_reply":"2024-07-21T17:49:59.272494Z"},"trusted":true},"execution_count":54,"outputs":[{"name":"stdout","text":"\nData Info:\n\nIndex: 2345 entries, 0 to 2350\nData columns (total 8 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Character 2345 non-null object\n 1 Universe 2345 non-null object\n 2 Strength 2345 non-null int64 \n 3 Speed 2345 non-null int64 \n 4 Intelligence 2345 non-null int64 \n 5 SpecialAbilities 2345 non-null object\n 6 Weaknesses 2345 non-null object\n 7 BattleOutcome 2345 non-null int64 \ndtypes: int64(4), object(4)\nmemory usage: 164.9+ KB\n","output_type":"stream"}]},{"cell_type":"code","source":"print(\"\\nData Description:\\n\", df.describe())","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.277702Z","iopub.execute_input":"2024-07-21T17:49:59.278701Z","iopub.status.idle":"2024-07-21T17:49:59.307577Z","shell.execute_reply.started":"2024-07-21T17:49:59.278655Z","shell.execute_reply":"2024-07-21T17:49:59.306185Z"},"trusted":true},"execution_count":55,"outputs":[{"name":"stdout","text":"\nData Description:\n Strength Speed Intelligence BattleOutcome\ncount 2345.000000 2345.000000 2345.000000 2345.000000\nmean 5.441365 5.481450 5.550107 0.278038\nstd 2.896110 2.858841 2.861892 0.448128\nmin 1.000000 1.000000 1.000000 0.000000\n25% 3.000000 3.000000 3.000000 0.000000\n50% 5.000000 6.000000 6.000000 0.000000\n75% 8.000000 8.000000 8.000000 1.000000\nmax 10.000000 10.000000 10.000000 1.000000\n","output_type":"stream"}]},{"cell_type":"code","source":"# Calculate IQR\nQ1 = df[['Strength', 'Speed', 'Intelligence']].quantile(0.25)\nQ3 = df[['Strength', 'Speed', 'Intelligence']].quantile(0.75)\nIQR = Q3 - Q1\n# Remove outliers\ndf = df[~((df[['Strength', 'Speed', 'Intelligence']] < (Q1 - 1.5 * IQR)) | (df[['Strength', 'Speed', 'Intelligence']] > (Q3 + 1.5 * IQR))).any(axis=1)]","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.309531Z","iopub.execute_input":"2024-07-21T17:49:59.310043Z","iopub.status.idle":"2024-07-21T17:49:59.331734Z","shell.execute_reply.started":"2024-07-21T17:49:59.309999Z","shell.execute_reply":"2024-07-21T17:49:59.329813Z"},"trusted":true},"execution_count":56,"outputs":[]},{"cell_type":"code","source":"# Normalize data using Quantile Transformer and check with Shapiro-Wilk test\nfor column in ['Strength', 'Speed', 'Intelligence']:\n qt = QuantileTransformer()\n df[[column]] = qt.fit_transform(df[[column]])\n # Check normalization with Shapiro-Wilk test\n stat, p = shapiro(df[column])\n print(f'\\nShapiro-Wilk Test for {column}: Statistics=%.3f, p=%.3f' % (stat, p))\n if p < 0.05:\n # Apply Power Transformer if not normally distributed\n pt = PowerTransformer()\n df[[column]] = pt.fit_transform(df[[column]])","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.333507Z","iopub.execute_input":"2024-07-21T17:49:59.333999Z","iopub.status.idle":"2024-07-21T17:49:59.412571Z","shell.execute_reply.started":"2024-07-21T17:49:59.333955Z","shell.execute_reply":"2024-07-21T17:49:59.411456Z"},"trusted":true},"execution_count":57,"outputs":[{"name":"stdout","text":"\nShapiro-Wilk Test for Strength: Statistics=0.947, p=0.000\n\nShapiro-Wilk Test for Speed: Statistics=0.948, p=0.000\n\nShapiro-Wilk Test for Intelligence: Statistics=0.948, p=0.000\n","output_type":"stream"}]},{"cell_type":"code","source":"# t-test between two groups (example)\nt_stat, t_p = ttest_ind(df[df['Universe'] == 'Marvel']['Strength'], df[df['Universe'] == 'DC Comics']['Strength'])\nprint('\\nT-test: t=%.3f, p=%.3f' % (t_stat, t_p))","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.417173Z","iopub.execute_input":"2024-07-21T17:49:59.417610Z","iopub.status.idle":"2024-07-21T17:49:59.431147Z","shell.execute_reply.started":"2024-07-21T17:49:59.417570Z","shell.execute_reply":"2024-07-21T17:49:59.429864Z"},"trusted":true},"execution_count":58,"outputs":[{"name":"stdout","text":"\nT-test: t=1.512, p=0.131\n","output_type":"stream"}]},{"cell_type":"code","source":"print(\"\\n--- T-tests ---\")\nt_test_results = []\nfor col1 in ['Strength', 'Speed', 'Intelligence']:\n for col2 in ['Strength', 'Speed', 'Intelligence']:\n if col1 != col2:\n t_stat, t_p = ttest_ind(df[col1], df[col2])\n t_test_results.append({\n 'Comparison': f'{col1} vs {col2}',\n 'T Statistic': t_stat,\n 'p-value': t_p\n })\n print(f'T-test between {col1} and {col2}: t-statistic={t_stat:.3f}, p-value={t_p:.3f}')","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.432771Z","iopub.execute_input":"2024-07-21T17:49:59.433181Z","iopub.status.idle":"2024-07-21T17:49:59.451964Z","shell.execute_reply.started":"2024-07-21T17:49:59.433145Z","shell.execute_reply":"2024-07-21T17:49:59.450527Z"},"trusted":true},"execution_count":59,"outputs":[{"name":"stdout","text":"\n--- T-tests ---\nT-test between Strength and Speed: t-statistic=-0.000, p-value=1.000\nT-test between Strength and Intelligence: t-statistic=0.000, p-value=1.000\nT-test between Speed and Strength: t-statistic=0.000, p-value=1.000\nT-test between Speed and Intelligence: t-statistic=0.000, p-value=1.000\nT-test between Intelligence and Strength: t-statistic=-0.000, p-value=1.000\nT-test between Intelligence and Speed: t-statistic=-0.000, p-value=1.000\n","output_type":"stream"}]},{"cell_type":"code","source":"print(\"\\n--- ANOVA ---\")\nanova_results = {}\nanova_stat, anova_p = f_oneway(df['Strength'], df['Speed'], df['Intelligence'])\nanova_results['ANOVA'] = {\n 'F-statistic': anova_stat,\n 'p-value': anova_p\n}\nprint(f'ANOVA: F-statistic={anova_stat:.3f}, p-value={anova_p:.3f}')","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.453747Z","iopub.execute_input":"2024-07-21T17:49:59.454130Z","iopub.status.idle":"2024-07-21T17:49:59.468533Z","shell.execute_reply.started":"2024-07-21T17:49:59.454097Z","shell.execute_reply":"2024-07-21T17:49:59.466905Z"},"trusted":true},"execution_count":60,"outputs":[{"name":"stdout","text":"\n--- ANOVA ---\nANOVA: F-statistic=0.000, p-value=1.000\n","output_type":"stream"}]},{"cell_type":"code","source":"# Boxplot\nplt.figure(figsize=(10, 6))\nsns.boxplot(data=df[['Strength', 'Speed', 'Intelligence']])\nplt.title(\"Boxplot of Strength, Speed, and Intelligence\")\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.470389Z","iopub.execute_input":"2024-07-21T17:49:59.470842Z","iopub.status.idle":"2024-07-21T17:49:59.753902Z","shell.execute_reply.started":"2024-07-21T17:49:59.470766Z","shell.execute_reply":"2024-07-21T17:49:59.752662Z"},"trusted":true},"execution_count":61,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Barplot\nplt.figure(figsize=(10, 6))\nsns.barplot(x='Character', y='Strength', data=df)\nplt.title(\"Barplot of Character vs Strength\")\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:49:59.755328Z","iopub.execute_input":"2024-07-21T17:49:59.755685Z","iopub.status.idle":"2024-07-21T17:50:00.286452Z","shell.execute_reply.started":"2024-07-21T17:49:59.755654Z","shell.execute_reply":"2024-07-21T17:50:00.284871Z"},"trusted":true},"execution_count":62,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"numerical_columns = ['Strength', 'Speed', 'Intelligence']\nfor column in numerical_columns:\n plt.figure(figsize=(10, 6))\n sns.histplot(df[column], kde=True)\n plt.title(f\"Histogram of {column}\")\n plt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:00.288154Z","iopub.execute_input":"2024-07-21T17:50:00.288546Z","iopub.status.idle":"2024-07-21T17:50:01.426954Z","shell.execute_reply.started":"2024-07-21T17:50:00.288513Z","shell.execute_reply":"2024-07-21T17:50:01.425714Z"},"trusted":true},"execution_count":63,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"iVBORw0KGgoAAAANSUhEUgAAA1IAAAIjCAYAAAAJLyrXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABjS0lEQVR4nO3dd3iV9f3/8dcZOedkhyRkQcLeIFMQtYjKEqtSqRaLFChKtaC1OFpqldFBHRV/WpRaK6gVV7+KioICijiQEZZC2EhYScjeJznn3L8/AqeGfYeEk/F8XNe5knOfz7nP+z53Qs6Lz7gthmEYAgAAAACcN2ugCwAAAACAhoYgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAjVDr1q01YcKEQJfR6D3xxBNq27atbDabevXqFehy6pWZM2fKYrEoOzs70KUAQJ0gSAFAPbdw4UJZLBZt2LDhtI8PHjxY3bt3v+DX+eijjzRz5swL3k9T8cknn+ihhx7SFVdcoQULFuivf/3rWdt/8MEHuuqqqxQXF6eQkBC1bdtWt956q5YtW+Zvc+TIEc2cOVObN2+u4+prz1//+lctXrw40GUAwEVHkAKARmjnzp3617/+Zeo5H330kWbNmlVHFTU+n376qaxWq/7973/rF7/4hUaOHHnGtk8++aRuvPFGWSwWTZ8+XXPnztXo0aO1e/duvfHGG/52R44c0axZswhSANAA2ANdAACg9jmdzkCXYFpJSYlCQ0MDXcZ5y8rKUnBwsBwOx1nbeTwe/elPf9LQoUP1ySefnHY/NVVaWqqQkJAaPx8AUHP0SAFAI3TyHKnKykrNmjVLHTp0kMvlUkxMjK688kotX75ckjRhwgTNmzdPkmSxWPy3E0pKSnT//fcrOTlZTqdTnTp10pNPPinDMKq9bllZme69917FxsYqPDxcN954ow4fPiyLxVJt2OCJ+TPbt2/Xz3/+czVr1kxXXnmlJGnr1q2aMGGC2rZtK5fLpYSEBP3yl79UTk5Otdc6sY9du3bp9ttvV2RkpJo3b65HHnlEhmHo4MGDuummmxQREaGEhAT9/e9/P6/37kTwadeunZxOp1q3bq0//OEPcrvd/jYWi0ULFixQSUmJ/71auHDhafeXnZ2twsJCXXHFFad9PC4uTpK0atUqXXrppZKkiRMnnrLfE0M4U1NTNWjQIIWEhOgPf/iDJMntdmvGjBlq3769nE6nkpOT9dBDD1Wr+UTdU6dO1eLFi9W9e3c5nU5169at2vDCE1atWqV+/frJ5XKpXbt2+uc//+l/z3+4v5KSEr388sv+ek+em5efn68JEyYoKipKkZGRmjhxokpLS898AgCggaBHCgAaiIKCgtNO3K+srDznc2fOnKk5c+bojjvuUP/+/VVYWKgNGzZo48aNGjp0qH71q1/pyJEjWr58uV599dVqzzUMQzfeeKM+++wzTZo0Sb169dLHH3+sBx98UIcPH9bcuXP9bSdMmKC33npL48aN02WXXabPP/9c119//RnruuWWW9ShQwf99a9/9Yey5cuXa9++fZo4caISEhK0bds2vfDCC9q2bZu++eabah/kJelnP/uZunTpor/97W/68MMP9ec//1nR0dH65z//qWuuuUaPPfaYXnvtNT3wwAO69NJLNWjQoLO+V3fccYdefvll/fSnP9X999+vtWvXas6cOUpLS9O7774rSXr11Vf1wgsvaN26dXrxxRclSZdffvlp9xcXF6fg4GB98MEHuueeexQdHX3adl26dNHs2bP16KOPavLkyfrRj350yn5zcnJ03XXXacyYMbr99tsVHx8vn8+nG2+8UV9++aUmT56sLl266Ntvv9XcuXO1a9euU4bdffnll3rnnXf061//WuHh4XrmmWc0evRopaenKyYmRpK0adMmjRgxQomJiZo1a5a8Xq9mz56t5s2bV9vXq6++6v+Zmjx5siSpXbt21drceuutatOmjebMmaONGzfqxRdfVFxcnB577LGzngcAqPcMAEC9tmDBAkPSWW/dunWr9pxWrVoZ48eP99/v2bOncf3115/1daZMmWKc7s/C4sWLDUnGn//852rbf/rTnxoWi8XYs2ePYRiGkZqaakgy7rvvvmrtJkyYYEgyZsyY4d82Y8YMQ5Jx2223nfJ6paWlp2x7/fXXDUnG6tWrT9nH5MmT/ds8Ho/RsmVLw2KxGH/729/82/Py8ozg4OBq78npbN682ZBk3HHHHdW2P/DAA4Yk49NPP/VvGz9+vBEaGnrW/Z3w6KOPGpKM0NBQ47rrrjP+8pe/GKmpqae0W79+vSHJWLBgwSmPXXXVVYYkY/78+dW2v/rqq4bVajW++OKLatvnz59vSDK++uor/zZJhsPh8J8zwzCMLVu2GJKMZ5991r/thhtuMEJCQozDhw/7t+3evduw2+2n/IyEhoae9n09cX5++ctfVtv+k5/8xIiJiTmlPQA0NAztA4AGYt68eVq+fPkpt0suueScz42KitK2bdu0e/du06/70UcfyWaz6d577622/f7775dhGFq6dKkk+YeH/frXv67W7p577jnjvu+6665TtgUHB/u/Ly8vV3Z2ti677DJJ0saNG09pf8cdd/i/t9ls6tevnwzD0KRJk/zbo6Ki1KlTJ+3bt++MtUhVxypJ06ZNq7b9/vvvlyR9+OGHZ33+mcyaNUuLFi1S79699fHHH+vhhx9W37591adPH6WlpZ33fpxOpyZOnFht29tvv60uXbqoc+fOys7O9t+uueYaSdJnn31Wrf2QIUOq9RpdcsklioiI8L83Xq9XK1as0KhRo5SUlORv1759e1133XWmj/3kc/yjH/1IOTk5KiwsNL0vAKhPGNoHAA1E//791a9fv1O2N2vW7JzX6pk9e7ZuuukmdezYUd27d9eIESM0bty48wphBw4cUFJSksLDw6tt79Kli//xE1+tVqvatGlTrV379u3PuO+T20pSbm6uZs2apTfeeOOUhRgKCgpOaZ+SklLtfmRkpFwul2JjY0/ZfvI8q5OdOIaTa05ISFBUVJT/WGvitttu02233abCwkKtXbtWCxcu1KJFi3TDDTfou+++k8vlOuc+WrRoccriFrt371ZaWtopw+5OOPk9PPn9kqp+hvLy8vzty8rKTnveznYuz+Tk12vWrJkkKS8vTxEREab3BwD1BUEKAJqAQYMGae/evXrvvff0ySef6MUXX9TcuXM1f/78aj06F9sPe59OuPXWW/X111/rwQcfVK9evRQWFiafz6cRI0bI5/Od0t5ms53XNkmnLI5xJifPw6pNERERGjp0qIYOHaqgoCC9/PLLWrt2ra666qpzPvd075fP51OPHj301FNPnfY5ycnJ1e5f6Htj1sV+PQC4WAhSANBEREdHa+LEiZo4caKKi4s1aNAgzZw50x+kzhQeWrVqpRUrVqioqKhar9SOHTv8j5/46vP5tH//fnXo0MHfbs+ePeddY15enlauXKlZs2bp0Ucf9W+vyZDEmjhxDLt37/b3uElSZmam8vPz/cdaW/r166eXX35ZR48elVSzANeuXTtt2bJF1157ba0EwLi4OLlcrtOet9Ntq8vQCQD1GXOkAKAJOHlIW1hYmNq3b19teewT13DKz8+v1nbkyJHyer36xz/+UW373LlzZbFY/PNmhg8fLkl67rnnqrV79tlnz7vOE70XJ/dWPP300+e9jwtx4qK6J7/eid6es61AeCalpaVas2bNaR87Mb+sU6dOks58Ds7m1ltv1eHDh097AeaysjKVlJSYqtdms2nIkCFavHixjhw54t++Z88ef70/FBoaaqpeAGgs6JECgCaga9euGjx4sPr27avo6Ght2LBB//3vfzV16lR/m759+0qS7r33Xg0fPlw2m01jxozRDTfcoKuvvloPP/ywvv/+e/Xs2VOffPKJ3nvvPd13333+hQv69u2r0aNH6+mnn1ZOTo5/+fNdu3ZJOr+ei4iICA0aNEiPP/64Kisr1aJFC33yySfav39/Hbwrp+rZs6fGjx+vF154Qfn5+brqqqu0bt06vfzyyxo1apSuvvpq0/ssLS3V5Zdfrssuu0wjRoxQcnKy8vPztXjxYn3xxRcaNWqUevfuLamqdykqKkrz589XeHi4QkNDNWDAgNPOJTth3Lhxeuutt3TXXXfps88+0xVXXCGv16sdO3borbfe0scff3zauXVnM3PmTH3yySe64oordPfdd/uDdPfu3bV58+Zqbfv27asVK1boqaeeUlJSktq0aaMBAwaYfp8AoKEhSAFAE3Dvvffq/fff1yeffCK3261WrVrpz3/+sx588EF/m5tvvln33HOP3njjDf3nP/+RYRgaM2aMrFar3n//fT366KN68803tWDBArVu3VpPPPGEfzW7E1555RUlJCTo9ddf17vvvqshQ4bozTffVKdOnc5rMQVJWrRoke655x7NmzdPhmFo2LBhWrp0abUV5OrSiy++qLZt22rhwoV69913lZCQoOnTp2vGjBk12l9UVJT+9a9/6cMPP9SCBQuUkZEhm82mTp066Yknnqi2GuKJOVPTp0/XXXfdJY/HowULFpw1SFmtVi1evFhz587VK6+8onfffVchISFq27atfvOb36hjx46ma+7bt6+WLl2qBx54QI888oiSk5M1e/ZspaWl+Yd0nvDUU09p8uTJ+uMf/6iysjKNHz+eIAWgSbAYzPYEANShzZs3q3fv3vrPf/6jsWPHBrocXIBRo0bVeBl9AGhsmCMFAKg1ZWVlp2x7+umnZbVaNWjQoABUhJo6+Vzu3r1bH330kQYPHhyYggCgnmFoHwCg1jz++ONKTU3V1VdfLbvdrqVLl2rp0qWaPHnyKctwo35r27atJkyYoLZt2+rAgQN6/vnn5XA49NBDDwW6NACoFxjaBwCoNcuXL9esWbO0fft2FRcXKyUlRePGjdPDDz8su53/u2tIJk6cqM8++0wZGRlyOp0aOHCg/vrXv6pPnz6BLg0A6gWCFAAAAACYxBwpAAAAADCJIAUAAAAAJjFgXZLP59ORI0cUHh5+XheMBAAAANA4GYahoqIiJSUlyWo9c78TQUrSkSNHWE0KAAAAgN/BgwfVsmXLMz5OkJIUHh4uqerNioiICHA1AAAAAAKlsLBQycnJ/oxwJgQpyT+cLyIigiAFAAAA4JxTflhsAgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASfZAF4BTpaenKzs7O9BlXLDY2FilpKQEugwAAACg1hGk6pn09HR17tJFZaWlgS7lggWHhGhHWhphCgAAAI0OQaqeyc7OVllpqcb+7gnFp7QLdDk1lpm+V6899qCys7MJUgAAAGh0CFL1VHxKO7Xs0C3QZQAAAAA4DRabAAAAAACTAhqk5syZo0svvVTh4eGKi4vTqFGjtHPnzmptBg8eLIvFUu121113VWuTnp6u66+/XiEhIYqLi9ODDz4oj8dzMQ8FAAAAQBMS0KF9n3/+uaZMmaJLL71UHo9Hf/jDHzRs2DBt375doaGh/nZ33nmnZs+e7b8fEhLi/97r9er6669XQkKCvv76ax09elS/+MUvFBQUpL/+9a8X9XgAAAAANA0BDVLLli2rdn/hwoWKi4tTamqqBg0a5N8eEhKihISE0+7jk08+0fbt27VixQrFx8erV69e+tOf/qTf/e53mjlzphwOR50eAwAAAICmp17NkSooKJAkRUdHV9v+2muvKTY2Vt27d9f06dNV+oOlwdesWaMePXooPj7ev2348OEqLCzUtm3bTvs6brdbhYWF1W4AAAAAcL7qzap9Pp9P9913n6644gp1797dv/3nP/+5WrVqpaSkJG3dulW/+93vtHPnTr3zzjuSpIyMjGohSpL/fkZGxmlfa86cOZo1a1YdHQkAAACAxq7eBKkpU6bou+++05dffllt++TJk/3f9+jRQ4mJibr22mu1d+9etWtXs+ssTZ8+XdOmTfPfLywsVHJycs0KBwAoPT1d2dnZgS7jgsXGxnLtOwDAeakXQWrq1KlasmSJVq9erZYtW5617YABAyRJe/bsUbt27ZSQkKB169ZVa5OZmSlJZ5xX5XQ65XQ6a6FyAEB6ero6d+mish8Mu26ogkNCtCMtjTAFADingAYpwzB0zz336N1339WqVavUpk2bcz5n8+bNkqTExERJ0sCBA/WXv/xFWVlZiouLkyQtX75cERER6tq1a53VDgCokp2drbLSUo393ROKT6nZSIH6IDN9r1577EFlZ2cTpAAA5xTQIDVlyhQtWrRI7733nsLDw/1zmiIjIxUcHKy9e/dq0aJFGjlypGJiYrR161b99re/1aBBg3TJJZdIkoYNG6auXbtq3Lhxevzxx5WRkaE//vGPmjJlCr1OAHARxae0U8sO3QJdBgAAF0VAV+17/vnnVVBQoMGDBysxMdF/e/PNNyVJDodDK1as0LBhw9S5c2fdf//9Gj16tD744AP/Pmw2m5YsWSKbzaaBAwfq9ttv1y9+8Ytq150CAAAAgNoU8KF9Z5OcnKzPP//8nPtp1aqVPvroo9oqCwAAAADOql5dRwoAAAAAGgKCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMsge6AAAXT3p6urKzswNdxgWLjY1VSkpKoMsAAABNGEEKaCLS09PVuUsXlZWWBrqUCxYcEqIdaWmEKQAAEDAEKeA8NIaenLS0NJWVlmrs755QfEq7QJdTY5npe/XaYw8qOzubIAUAAAKGIAWcQ2PqyZGk0Oh4tezQLdBlAAAANGgEKeAcsrOzG0VPTtq6z7X05f+n8vLyQJcCAADQ4BGkgPMUn9KuQffkZKbvDXQJAACgljWG6QdSw1xIiiAFAAAANECNafpBQ1xIiiAFAABQx+g1QF1oLNMPGupCUgQpAACAOkSvAepaQ59+0FARpAAAAOoQvQZA40SQAgAAuAjoNQAaF2ugCwAAAACAhoYgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEsufAwCAeis9PV3Z2dmBLuOCpKWlBboEAHWAIAUAAOql9PR0de7SRWWlpYEupVYUFxcHugQAtYggBQAA6qXs7GyVlZZq7O+eUHxKu0CXU2Np6z7X0pf/n8rLywNdCoBaRJACAAD1WnxKO7Xs0C3QZdRYZvreQJcAoA4QpAAAANDkMP8OF4ogBQAAgCaF+XeoDQQpAAAANCnMv0NtIEgBANDINIYhSxLDllD3mH+HC0GQAgCgEWlsQ5Ykhi0BqJ8IUgAANCKNZciSxLAlAPUbQQoAgEaooQ9Zkhi2BKB+swa6AAAAAABoaAhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIlV+wAggBrDhVO5aCoAoCkiSAFAgDS2C6dy0VQAQFNCkAKAAGksF07loqkAgKaIIAUAAdbQL5zKRVMBAE0Ri00AAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwKaBBas6cObr00ksVHh6uuLg4jRo1Sjt37qzWpry8XFOmTFFMTIzCwsI0evRoZWZmVmuTnp6u66+/XiEhIYqLi9ODDz4oj8dzMQ8FAAAAQBMS0CD1+eefa8qUKfrmm2+0fPlyVVZWatiwYSopKfG3+e1vf6sPPvhAb7/9tj7//HMdOXJEN998s/9xr9er66+/XhUVFfr666/18ssva+HChXr00UcDcUgAAAAAmgB7IF982bJl1e4vXLhQcXFxSk1N1aBBg1RQUKB///vfWrRoka655hpJ0oIFC9SlSxd98803uuyyy/TJJ59o+/btWrFiheLj49WrVy/96U9/0u9+9zvNnDlTDocjEIcGAAAAoBGrV3OkCgoKJEnR0dGSpNTUVFVWVmrIkCH+Np07d1ZKSorWrFkjSVqzZo169Oih+Ph4f5vhw4ersLBQ27ZtO+3ruN1uFRYWVrsBAAAAwPmqN0HK5/Ppvvvu0xVXXKHu3btLkjIyMuRwOBQVFVWtbXx8vDIyMvxtfhiiTjx+4rHTmTNnjiIjI/235OTkWj4aAAAAAI1ZvQlSU6ZM0Xfffac33nijzl9r+vTpKigo8N8OHjxY568JAAAAoPEI6BypE6ZOnaolS5Zo9erVatmypX97QkKCKioqlJ+fX61XKjMzUwkJCf4269atq7a/E6v6nWhzMqfTKafTWctHAQAAAKCpCGiPlGEYmjp1qt599119+umnatOmTbXH+/btq6CgIK1cudK/befOnUpPT9fAgQMlSQMHDtS3336rrKwsf5vly5crIiJCXbt2vTgHAgAAAKBJCWiP1JQpU7Ro0SK99957Cg8P989pioyMVHBwsCIjIzVp0iRNmzZN0dHRioiI0D333KOBAwfqsssukyQNGzZMXbt21bhx4/T4448rIyNDf/zjHzVlyhR6nQAAAADUiYAGqeeff16SNHjw4GrbFyxYoAkTJkiS5s6dK6vVqtGjR8vtdmv48OF67rnn/G1tNpuWLFmiu+++WwMHDlRoaKjGjx+v2bNnX6zDAAAAANDEBDRIGYZxzjYul0vz5s3TvHnzztimVatW+uijj2qzNAAAAAA4o3qzah8AAAAANBQEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJPsgS4AAAAAZ2cYhrw+Qx6fIY/XUKXPJxk/aGCp3t5msSjIZpXdZpHdapHFclIDABeMIAUAAFCHDElWV5jKfDZlFJTL7fHK7fEdv3lV4fHJXemT2+uTu/L4/eM3j9dXFZ58xjlf52xcdqtcQTa5gmwKcdgU5rIrzGlXuMuuqGCHmoUGyWm31c4BA00EQQoAAOA8eHxVgae80qtyT1XoKa/0qdzj/cH249sqq8JSeaVXbnVW8m/e0Lpyad2Ggxdch9Ui2a1WndzJZPzgG+/xHqwTyj0+lXt8UlnlGfcb4rApJtShuAiX4sKdio9wKcJlpzcLOAOCFAAAaDIMw1Cl1zgl/PwwIJVXeqsC0PGQVF5Z1XNU6a1pr1BVELHJp2CnQ64gq5x2m5x2q5x2qxz2/913BFmPb7fJYbfKYbPKbrUcH6JX9b3Ven7B5sSxVnpPHFPV8ZS4PSp2e1Rc7lFhuUf5pRUqqfCqtMKr0ooyHcwr8+8j1GFTi2bBSm4WIrunhocPNFIEKQBAg+H1GSqp8KiswquySq/KK6r+17/S61PF8SFQfid95rVYJIet6kPriQ+ojh98iK3wXdxjQe3w+Hz+n4czfS2t+GEo8uoCR8nJZbfKGWSTK8gql90mZ9DxYXP2qm3OIFu1oXQ7v1mut594SL+Y8Zx6Dbyqdg78PFgsFjnsFjnsVoU6z/6Rz+3xKq+0UtnFbmUVupVZWK6c4qqAtSuzWLsyiyU5lPjLeVr0bZHscfnq0SKS3io0aQQpAEC94vH6lFdaqdySCuWWVCivtEKF5ZUqLveopMJbh6/sUMr972rykiy1XPOVmoc71TzcqbhwpxIjXUqIDFZipEuJkS6Fu4LqsI6mrdJbFYxKK73KVahCu1+jg5WhKt6TfdqgVOGtWQK2WuQPP/4gdDwYuYKObztNMHLarabDg0NeyVe/u3OcdpsSImxKiHBJSVXbPF6fMgrLdTCvTIfySnU0v0yO5q3037Ri/TftK6VEh+jmPi00uk9LJUeHBPYAgAAgSAEAAsIwDBWVe5RZWK7MIrc/OBWWVZ7cmVSN1SIFO2wKDrIp2GGT025TkM1SNQTKVv2qHj/8uOszDFV4farwHL/94Pvy418t9iBll3qVXZp/1trDnPbj4cp1PFwF++8nRQUrIdKlcCdzSwzDkNvjqx5+ztJzVFbhPWlRhRTFXj9N+yolHcg74+ucCEUnfi5CfvD9ia8u/60qELGS3bnZbVa1bBails1CJMVo385tWvD8M7rx7j9qS1al0nNL9fSK3Xp6xW4NaBOtCZe31tCu8af8HgKNFUEKAHBRlFd6q0JToVsZheXKLCxX6Rl6mJx2q6JDHVW3EIcigoMU7qpaYSw4yFYnH4AP7Nqmf/zhV3r1v+8rOqm1jhW5lVXkVlZhuTIKy3U0v1xHC8pUWF41v2R3VrF2ZxWfcX+hDpsSo44HrAjX/76PdCkpMlgxYQ5FBQc1mA+dHq+v2kpzbs//5t2cHIjKjw+nK/d4ZdRgGJ3NalFwkE2Gu1jZ+7erVfvOSkpKUrDj9CGpJr1EMM9hlUq2r9IDl/9dXbr31MfbMvTf1EP6am+21u7P1dr9uWoRFayJV7TWrZcmK4KeWzRyBCkAQJ0orfDocH6ZDueV6VBemXJKKk5pY7VIsWFVq4PFhFWFpuhQh0IcdROWzsZmkbyFx9QpxqE+3RLO2K7E7dHRgnJlFFQFq6MF5cdvZce3laugrFIlFV7tySrWnrOELUmKcNnVLNShZiEONQsJUrMQh8JddoU47QoJslV9dVQtWR3qsMthr1pwwHZ8AQKb9X/3DUPam1cpR0IH5bgtsuaXyTAkQ/+7BlGl1yeP9wff+4yqJbaPX5vI4zV+sPz2/5bp9l7AxCKHzapgR1VvUPBpglBVQLL77wfZqnqLUle+r9feelQjZr2gXh171vj1UfuCHTaN6t1Co3q30JH8Mi1am67X1h7Q4fwy/fnDND2zcrcmD2qrCVe0Udg55mcBDRU/2QCAWlFhWLU7q+iswSkyOEgJES7FRziVEOlS8zBng+mROSHUaVf7uDC1jws7Y5sSt0cZhVVh60j+8YBVWK6j+VXBK6OwXPmlVctQFx5fOe1ATmmt1Zg4fq5WZUrKPFRr+zzhxEpzzuM9QcFBpw6h+2FAcgVZZbc2rHMMc5KigvXA8E6aek17Ld50WC9+uV97sor15Ce79O8v9+tXV7XThMtbyxXEdarQuBCkAAA1cqLHaa/ilfjLf2hNWYL0bUa1NjGhDrVsFqwWzYLVIipYIY6m8Wcn1GlXu+Zhatf8zGHL4/WpoKxSeaUVyiutVF5JhfJLK5VbWqESt+f4UtQelbi9//u+wqvK471DHl/V10qv4b8vWeTzViorM0MRzZoryOGQRVUrFtqsFgX5l9K2Kuj4V7vNoiBr1dcTS2z7w9LxJbidx5fkdtgYQoczcwXZNKZ/im7pl6wlW4/o/63YrX3ZJfrb0h36zzcH9Mfru2h4twR+htBoNI2/aACAC1Za4dHhvDIdzj+5xylajubRkppucKoJu82qmDCnYsKctbrfjRs3qm/fkfrZvHfUskPHWt03cD5sVotu6tVC1/dI1OLNR/T3T3bqUF6Z7vrPRl3eLkYzb+ymjvHhgS4TuGD8hQMAnFZReaV/jtPh/DLlHR+K9kMxoQ45SjK09d35uvHnv1T/y34UgEoB1Ed2m1U/7dtSI3skaP6qvZq/ep++3puj65/5Qvdc00F3D26noAY2tBf4IYIUAECGYaiwvKrH6VB+qY7kVy2YcLKYMIdaRAVX9Tod73FKXblF3+z6Wg7LhItfOIB6L8Rh17RhnXRLv2TN+mCbVqRl6anlu/Txtgw98dOe6poUEegSgRohSAFAE+T2eJVV6Fbm8aW9MwvdKnZXv2CoRVLzcKdaNAtWy6hgJUUFM1kcQI0lR4foX7/op/e3HNGM97dp25FC3fiPL/XA8E6a/KO2slqZO4WGhSAFAI1ceaVXOcUVyi52K7OoXJkFbuWWnn4p8vgIl1pEVc1xSox0yWknOAGoPRZL1fypy9vF6pHF32nZtgz9bekOrdmbo6du7VnrcwaBukSQAlCveH2G/8KeJ1Yl8/iqViXz+gwdK7YqrOdwrdhXqv3GoaoVx46vRBZksyro+PVqwl12hTntCnVWfbU1gf/pLK/0Kr+sUrnFFcopcSunuEI5JRWn9DSdEO6yH1+KvGo58vgIF/MVAFwUzcOdev72Pnpz/UHNeH+bPt91TCOf+UL/b0xvXdY2JtDlAeeFIAXgovF4fcovq1TB8VthWeXxZZ2rlnYurai6+OfZ2RUz4h49t6FA2rDlvF87xGFTmNOucJddkcFB/lvEGb7/4bbQAFwc9mS+4wHzxHtV9f55VFBe9T4WlFWe9b0Ld9kVE+pQXITLfx0nVtQDEEgWi0Vj+qeoV0qUpi7apD1ZxRr74lrNvKGrxg1sHejygHPiryiAWmcYhordHmUWunWsyK2cEreyiytOu3jB6VgsUnCQTUE2q2wWi2w2S9VXq0We8hLt/3a9fjRokELCwuXxVl0/p/L4V4/XUGmFV8Vuj4rLParwVoWLE4Etq8ht+njsVos/ZFULXsdDWZjLLoft+AVKbdaq6+7Yq77abVb5DEMyJEOGDEPyGVXv0e5DZQrtfo32FlmVcSBXlR5DlT6fKj0+VXh9Kq2o6pkrrfCqrNJ7XrWGOGyKDnUoJtSh2DCnYsIcig51MEQPQL3VOSFC70+9Qn9451st3nxEj7y3TTsyijTzxm70kqNeI0gBuGA+n6FjxW7/MtkZheUqrTj9B3+n3VqtxyfUaVeIw6YQh03BQTaFOO1y2c980c9Du7dp3Tt/0sMPp6pPnz7nrM3t8arE7VVxuUeF5ZUqKvf4e8MKyipVWP6/HrKCar1lHhWWVarC65PHZyi3pEK5JafOK7pQsddP0+Y8SXk559U+OKjqvYo4KcyduM+HDgANUYjDrrk/66XOiRF6bNkOvbY2XXuPFev5sX3VLNQR6PKA0yJIAaiRgrJKHcgp0YGcUh3KK/P3/JxgsVRdYyg+wlXVMxJa1TMScpGHyTntNjntVb00ZhmGofJK30kB69TQVeKu6vmq8Pjk9vjk9nj933u8hiyWqvfDarHIoqrhLBaLVF5aoo3r1qh9tz6KiIr0z/EKslnkOD7XK8Rh94fMYIdN1gAPMQSAumKxWHTXVe3UIS5M976+Sd/sy9VP53+tVyYNUIuo4ECXB5yCIAXgvBiGoawit/ZkFWvvseJTLs7qsFurVnuLqlrtrXm4s8H3jlgsFgU7qgJMQqSr1ve/ceNG9X1wpm4f/I5adkio9f0DQEN0bZd4vfPrKzRhwTrtPVainz7/tV75ZX91iA8PdGlANQQpAGeVU+xWWkaRdmUWqaj8f6u/WSxSUmSwWsWEqFV0iGLDnfSWAABqRaeEcP3f3ZfrFy+t056sYv10/hq9NOFS9W3VLNClAX4EKQCnKK/0akdGkdKOFlZbnMFutah1bKjaNw9T69gQFjAAANSZpKhgvf2rgfrly+u1KT1fY1/8Ri9NuFSXt4sNdGmAJIIUgB/IKizX1sMF2plRJI/PkFR1kdY2saHqnBCh1jEhsjfw4XoAgIajWahDr90xQHf9Z6NW7zqmXy5cr5fGX6rL2xOmEHgEKaCJMwxD+3NKlPp9no4UlPu3x4Y51D0pUh3jwxXsoOcJABAYIQ67XhjXV3f9J1Wrdh7TxIXr9dKES3UFYQoBRpACmiifz9CuzCJtOJCnnOPLelstUvu4MPVsGaXESFfAL0ILAIAkuYJs+ue4vrr7Pxv16Y6sqp4pwhQCjCAFNDGGIe3OKtKavTn+lfccNqt6tIhUr5QohTn5ZwEAUP847TY9f3sf/fo/G7VyR5bufGWD/nPHAPVJYQEKBAaTHYAmxJnSQ5vcsfro2wzllVbKZbdqYLsY/fKK1rqyQywhCgBQrzntNj13ex/9qEOsSiu8mrhgvXZkFAa6LDRRBCmgCSgsr1SaWijhtjkq8jkUZLOof+toTbiitfq3jpYziDlQAICGwWmvGubXJyVKBWWVGvfvdUrPKQ10WWiCCFJAI+bx+bRuf65eXXNAOYqQ4fMqyV6iCZe31sB2MSxfDgBokEIcdi2Y0F+dE8J1rMitsf/+RllF5ed+IlCLCFJAI5VZWK431h3Umn058vgMRahURxf+Rh0cBQpxMIQPANCwRYYE6ZVf9ldKdIgO5pbpjpc3qLTCc+4nArWEIAU0Mh6fT1/vzdabGw4qp6RCwUE2De8Wrx46oMpj3we6PAAAak1chEsv/7K/moUEaeuhAt37+mZ5j18HEahrBCmgEcktqdCb6w9q/fd5MgypY1yYxl3WSp0TIsRC5gCAxqhNbKj+9Yt+ctitWpGWqT8t2R7oktBEEKSARiLtaKHeWJ+u7OKqXqiRPRJ0XY9ELqYLAGj0+rWO1txbe0mSFn79vV76cn9gC0KTwEQJoIGr9Pq0aucxbT9atfxry2bBGtEtQaEsZQ4AaEKuvyRRh/I6a87SHfrzh9vVPi5Mgzo2D3RZaMTokQIasOJyj/6bekjbjxbKIumyNtH6Se8WhCgAQJM0eVBb3dK3pXyGNHXRRu07VhzoktCIBTRIrV69WjfccIOSkpJksVi0ePHiao9PmDBBFoul2m3EiBHV2uTm5mrs2LGKiIhQVFSUJk2apOJifmnQ+GUUluuN9enKKnIrOMimn/RuoQFtY2S1MBsKANA0WSwW/fkn3dUnJUqF5R7d8coGFZZXBrosNFIBDVIlJSXq2bOn5s2bd8Y2I0aM0NGjR/23119/vdrjY8eO1bZt27R8+XItWbJEq1ev1uTJk+u6dCCgdmUW6b+ph1RS4VVMqEM/uzRZydEhgS4LAICAc9ptmj+urxIjXdp3rES/eX0TK/mhTgR0/M91112n66677qxtnE6nEhISTvtYWlqali1bpvXr16tfv36SpGeffVYjR47Uk08+qaSkpFqvGQi0zQfz9fmuY5Kk1jEhGtE9gQvrAgDwA3HhLr0wrp9+Ov9rfbbzmJ5ZuVu/Hdox0GWhkan3c6RWrVqluLg4derUSXfffbdycnL8j61Zs0ZRUVH+ECVJQ4YMkdVq1dq1a8+4T7fbrcLCwmo3oL4zDEPf7Mvxh6ieLSN1Q88kQhQAAKfRo2Wk/ja6hyTpmU93+/9+ArWlXgepESNG6JVXXtHKlSv12GOP6fPPP9d1110nr9crScrIyFBcXFy159jtdkVHRysjI+OM+50zZ44iIyP9t+Tk5Do9DuBCGYahz3cd09r9uZKky9pG66qOzZkPBQDAWfykd0v9fECKDEO6741NOpJfFuiS0IjU6yA1ZswY3XjjjerRo4dGjRqlJUuWaP369Vq1atUF7Xf69OkqKCjw3w4ePFg7BQN1wDAMrUjL0pZDBZKkwR2ba0CbGFkIUQAAnNOjP+6q7i0ilFdaqamLNqrC4wt0SWgk6nWQOlnbtm0VGxurPXv2SJISEhKUlZVVrY3H41Fubu4Z51VJVfOuIiIiqt2A+sgwDH12/BpRFknDu8arZ3JUoMsCAKDBcAXZ9NzP+yrcZdfG9Hz9bemOQJeERqJBBalDhw4pJydHiYmJkqSBAwcqPz9fqamp/jaffvqpfD6fBgwYEKgygVphGIZW78rWt4ereqKGdYtX50RCPwAAZqXEhOipW3tJkl76ar/WHGKIHy5cQINUcXGxNm/erM2bN0uS9u/fr82bNys9PV3FxcV68MEH9c033+j777/XypUrddNNN6l9+/YaPny4JKlLly4aMWKE7rzzTq1bt05fffWVpk6dqjFjxrBiHxo0wzD01d4cbT6UL0ka0iVOnRMIUQAA1NTQrvH61aC2kqR/rCuQvRmfFXFhAhqkNmzYoN69e6t3796SpGnTpql379569NFHZbPZtHXrVt14443q2LGjJk2apL59++qLL76Q0+n07+O1115T586dde2112rkyJG68sor9cILLwTqkIBasTE9X6kH8iRJV3dqrm5JkQGuCACAhu+B4Z3Uv3W0yjyGmo+aLi/TpXABAnodqcGDB8swznyBtI8//vic+4iOjtaiRYtqsywgoHZmFOnLPdmSpCvbx+qSllGBLQgAgEYiyGbVsz/vrWF//0wFcW20Oc+rVoEuCg1Wg5ojBTR2B3NL9cn2qqX7eyVHqU9KVGALAgCgkYmPcGnaZVEyfF59X2JT2lGuJ4qaIUgB9UR2sVtLth6Vz5Dax4VpUIdYljgHAKAO9Ih3quCr1yVJn+3MUn5pRYArQkNEkALqgdIKj97fckQVXp+Solwa3jWeEAUAQB0qWPOWYp0+VXoNLduWIa/vzNNNgNOpUZBq27atcnJyTtmen5+vtm3bXnBRQFPi9Rla+m2Giso9igwO0g2XJMlu4/84AACoU4ZPl8Z45LRblVno1jf7Tv1sC5xNjT6tff/99/J6vadsd7vdOnz48AUXBTQlX+w+pkP5ZQqyWXTDJYlyBdkCXRIAAE1CiF26tkucJGnDgTwdzC0NcEVoSEyt2vf+++/7v//4448VGfm/JZm9Xq9Wrlyp1q1b11pxQGO37UiBthyquuDu8G4JiglznuMZAACgNnWIC1f3pFJ9d6RQH2/P0NgBrRTMf2riPJgKUqNGjZIkWSwWjR8/vtpjQUFBat26tf7+97/XWnFAY5ZRWK7PdhyTJF3WJlrtmocFuCIAAJqmQR2b63B+mfJKK7UyLVPX90hkrjLOydTQPp/PJ5/Pp5SUFGVlZfnv+3w+ud1u7dy5Uz/+8Y/rqlag0XBXerX026PyGobaNQ9V/zbRgS4JAIAmK8hm1YjuCbJZLNp7rETfHi4IdEloAGo0R2r//v2KjY2t7VqAJsEwDC1Py1RhuUcRLruGdmGFPgAAAi0u3KXL28dIklbvzlZOsTvAFaG+MzW074dWrlyplStX+numfuill1664MKAxmrLoQLtPVYiq0Ua2SNRTsZhAwBQL/ROjlJ6TqkO5JZq6bYMjemXzEq6OKMa/WTMmjVLw4YN08qVK5Wdna28vLxqNwCnl1lYri92V82L+lGH5oqPcAW4IgAAcILFYtHQrvEKDrIpp7hCX+1hSXScWY16pObPn6+FCxdq3LhxtV0P0GhVeHxa+l2GfIbUrnmoeraMPPeTAADARRXqtGto13i9v+WINh/KV0pMiNrEhga6LNRDNeqRqqio0OWXX17btQCN2urdx1RQVqkwJ/OiAACoz9rEhqpXcpQkafn2TJW4PYEtCPVSjYLUHXfcoUWLFtV2LUCjte9YsbYdKZQkDe8Wz7woAADquSvaxSg2zKGySq8+2Z4pwzACXRLqmRoN7SsvL9cLL7ygFStW6JJLLlFQUFC1x5966qlaKQ5oDErcHq1Iy5Ik9UmJUstmIQGuCAAAnIvdZtWIbgl6Y/1BpeeWalN6vvq0ahboslCP1ChIbd26Vb169ZIkfffdd9UeY7gS8D+GYWhFWqbKKr2KCXNoYLuYQJcEAADOU0yYU4M6NNenO7P01d5stWgWzEJR8KtRkPrss89quw6gUdp2tFDf55TKZrFoRLcE2a0soQoAQEPSvUWEDuSWaO+xEi39LkM/758ih52/56jhHCkA51Zc7tEXu7IlSZe1i1ZsmDPAFQEAALMsFouGdIlXmNOugrJKfbYzK9AloZ6oUY/U1VdffdYhfJ9++mmNCwIaA8MwtHJHpiq8PsVHONUnhTHVAAA0VK4gm0Z0T9D/pR7SjowipUSHqEtiRKDLQoDVKEidmB91QmVlpTZv3qzvvvtO48ePr426gAZtZ0aRf0jf0C7xsjJ3EACABq1FVLAGtI3WN/ty9dnOLCVEutQsxBHoshBANQpSc+fOPe32mTNnqri4+IIKAhq6ErdHq3YdkyT1bxutGIb0AQDQKFzaOlqHcst0KL9MS7/L0K39WjL/uQmr1TN/++2366WXXqrNXQINzqqdx+T2+BQX7lRfhvQBANBoWC0WDe+WIFeQVceK3PpqT06gS0IA1WqQWrNmjVwuloRE07XvWLH2HCuW1SIN6RIvm5UhfQAANCZhLruGdo2XJG0+mK/92SUBrgiBUqOhfTfffHO1+4Zh6OjRo9qwYYMeeeSRWikMaGgqvT7/kL7eKc3UPJwhfQAANEZtY8PUKzlKmw/ma/n2TP18QIrCnDX6WI0GrEZnPDIystp9q9WqTp06afbs2Ro2bFitFAY0NGv356qo3KNwl10D2kQHuhwAAFCHrmgfo8P5ZTpW5NbH2zL0k94tWFyqialRkFqwYEFt1wE0aNnFbm1Kz5MkDe7YXEE2Jp4CANCY2a1WXdc9Qa+vS9ehvDKt3Zerge1iAl0WLqIL6oNMTU1VWlqaJKlbt27q3bt3rRQFNCSGYeizHVnyGVK75qFq2zws0CUBAICLoFmIQ9d2jteybRla932uEiJdahMbGuiycJHUKEhlZWVpzJgxWrVqlaKioiRJ+fn5uvrqq/XGG2+oefPmtVkjUK9tP1qoIwXlCrJZNKgjP/sAADQlnRLCdaSgTFsPFejjbRn6ef8URQQHBbosXAQ1Gn90zz33qKioSNu2bVNubq5yc3P13XffqbCwUPfee29t1wjUW2UVXn25O1uSdFmbGEW4+IcTAICm5kcdYhUf4ZTb49OH3x6Vx+sLdEm4CGoUpJYtW6bnnntOXbp08W/r2rWr5s2bp6VLl9ZacUB99+WebJV7fIoNc6hnclSgywEAAAFgt1o1skeiXEFWZRW5tWrXMRmGEeiyUMdqFKR8Pp+Cgk79n/egoCD5fCRwNA2H88q0/WihJOmaznFcMwoAgCYswhWkEd0SZJG07Uihth4qCHRJqGM1ClLXXHONfvOb3+jIkSP+bYcPH9Zvf/tbXXvttbVWHFBfeX2GPt2ZJUnqnhShxMjgAFcEAAACrVVMqK5oHytJ+nz3MR3MLQ1wRahLNQpS//jHP1RYWKjWrVurXbt2ateundq0aaPCwkI9++yztV0jUO9sTM9TbkmFgoNs/n8wAQAA+qREqXNCuAxD+ujboyooqwx0SagjNVq1Lzk5WRs3btSKFSu0Y8cOSVKXLl00ZMiQWi0OqI8Kyyu1bn+upKrJpa4gW4ArAgAA9YXFYtG1neOUV1qhzEK3PthyRLf0aymnnc8LjY2pHqlPP/1UXbt2VWFhoSwWi4YOHap77rlH99xzjy699FJ169ZNX3zxRV3VCtQLX+7OlsdnKCnKpc4J4YEuBwAA1DN2m1U/7pGkEIdNOSUV+vDbo/L6WHyisTEVpJ5++mndeeedioiIOOWxyMhI/epXv9JTTz1Va8UB9c3B3FLtziqWRdLgjnGyWFhgAgAAnCrMZddNPZMUZLPoYG6ZVqRlspJfI2MqSG3ZskUjRow44+PDhg1TamrqBRcF1Ec+Q/p81zFJUo+WkWoe7gxwRQAAoD6Li3BpZI9EWSzSjowirdmXE+iSUItMBanMzMzTLnt+gt1u17Fjxy64KKA+2ltkVU5JhVxBVg1sGxPocgAAQAPQOiZU13SOkySt/z5PWw7lB7Yg1BpTQapFixb67rvvzvj41q1blZiYeMFFAfWNNSRSaQVVk0Qvb8cCEwAA4Px1T4rUgDbRkqRVO49p2xGuMdUYmApSI0eO1COPPKLy8vJTHisrK9OMGTP04x//uNaKA+qLZleNV6VhUVy4U92STp0jCAAAcDYD2kSrV3KUJGlFWpZ2HC0MbEG4YKaWP//jH/+od955Rx07dtTUqVPVqVMnSdKOHTs0b948eb1ePfzww3VSKBAou3MqFHbJMEnS4E7NZWWBCQAAYJLFYtGgDrHy+gx9e7hAn2zPlNVqUcd4VgBuqEwFqfj4eH399de6++67NX36dP/KIxaLRcOHD9e8efMUHx9fJ4UCgeDzGfrXpqr/MUoJ9SoxMjjAFQEAgIbKYrHo6k7N5TMMbTtSqGXbMuTxGurKaJcGyfQFeVu1aqWPPvpIeXl52rNnjwzDUIcOHdSsWbO6qA8IqP+mHtKe3Er53KXq0aJG168GAADwO3HBXsOQth8t1PK0TJVUeNSvVTMuq9LA1PiTYbNmzXTppZfWZi1AvVJQVqnHlu2QJOV/9bpcHcYFuCIAANAYWCwWDekSp2CHTakH8vT13hyVur0a1DGWMNWAmFpsAmhKnl6xSzklFWoRblNR6geBLgcAADQiFotFV7aP1aAOsZKkzYfy9eG3R+X2eANcGc4XQQo4jZ0ZRXplzQFJ0qTekZLPE+CKAABAY9Q7pZlGdEuQ1SLtPVai19cd1LEid6DLwnkgSAEnMQxDj7z3nbw+QyO6JahXgjPQJQEAgEasU0K4bumbrHCXXQVllXpzw0FtP1LoX9gN9RNBCjjJ+1uOaN3+XLmCrHrkhq6BLgcAADQBCZEu3dY/Ra1iQuT1GVqelqkPth5VUXlloEvDGRCkgB8oKq/UXz5MkyRNvbq9WkSx3DkAALg4goNsuqlnkga2jZHVIu3PLtGr3xzQpvQ8+eidqndYz7lesqiwwqLvjhQor6RCNqtFdptVQVaLIoOD1LJZiBx2MnBdeGblbmUVudU6JkR3Dmob6HIAAEATY7FY1L9NtNo1D9XKHVk6WlCu1buzte1IoS5tHa0O8WGysrJfvUCQqkfSjhZq5qocJd/3hpZnBEkZWadtZ7VISVHBah0Tqi6J4QpxcBprw67MIr301feSpBk3dpPTbgtsQQAAoMmKCXPqlr4t9d3hQn21N1s5JRVati1D3+wLUr/WzdQxPvyi1VLh8amgrFIFZZUqLKtUsdujco9X7kqf3B6fJMlmtchmtchhtyoqOEjRoQ41C3EoOtQhm7VxBj8+gdcjoQ67tmZVyOoMlc1iKDEyRLHhTsmQKn0+VXp8yixyq6CsUofyynQor0zf7MtRz+Qo9UmJIlBdAMMw9OjxBSaGdY3X1Z3iAl0SAABo4iwWi3q0jFTH+DBtOVSgTel5yi+r1Iq0LK3aeUzNlKTg9v3lq6VRf+WVXuWWVCivtEK5JRXKKalQTnGFit01X73YYbOqVUyI2saGqnVsqFxBjec/qvnkXY8kRwdrSr9IPfzrcZoy4ymldGx5ShvDMJRfVqkDOaVKO1qorCK3Ug/kaeuhfPVKjlL/1tGy2xj2Z9YHW4/qm325ctqteuTHLDABAADqD2eQTf3bRKtXcpS+PVygrYfyVVju0TFFKm70o/qyzNCu9elKiHApPsKlMKddoU67Qh022W1WGTIkQ/IahsoqvCqr9Kq0wquCskrllVQor7RSuSUVKqs88zWsXEFWRQYHKTI4SOHOIDmDrHIF2eQ8Pt3E6zPk9Rkqq/Qqv7TSH8bcHp92ZxVrd1axrBapc0KE+rVqpmahjov19tUZglQ9YrFYdG3bED107HudqQfUYrGoWUhVV2nPlpHan1OitftylVXk1vrv87TvWImGdYtXXLjr4hbfgBW7PfrLh9slSVOubq/k6JAAVwQAAHAqh92qvq2aqU9KlDIL3fpiwxalFxmyh8cos9CtzEK3pIILeo0wp/34sLwgxYQ6FR3mUEyoo0Y9SYZhKLPQrX3Zxdp3rEQ5JRXafrRQ248Wqn1cmAa0iVZsWMO9zAxBqgGzWCxqGxumNjGh2nOsWJ/tOKackgq9uf6gBrSNUb+UZrI20jGptenZlbuVWehWq5gQTWaBCQAAUM9ZLBYlRLrUVpla89yDumXGvxXdrqcyCsuVXeRWSYVHJRVeVRyfv/RDdqtFIQ6bgh02hTuPz2UKDfL/R31tLmh2os6ESJcubxerowVl2vB9nvZll2hPVrH2HStWv1bRatFAFyQkSDUCFotFHeLC1SIqWJ/uyNLeYyVaszdHh/PKNLJ7gpyNaCxqbduTVaR/f7lfkjTjhq6NatwuAABoGoKtXnVKCFenhOoLUHi8Pnl8hiwWySKLLJaqIGUJ0Kp/iZHBuqFnsLKL3fpmX472HivRuu9zFRFklyO+XUBquhBMpmlEQhx2Xd8jUcO6xstutSg9t1Rvbjio/NKKQJdWLxmGoRnvb5PHZ2hIlzhd0zk+0CUBAADUGrvtxDwmmxx2q4Js1oCFqB+KDXPqx5ckaWT3BAUH2VRYaVXCL57SO2nFgS7NFIJUI2OxWNQlMUK39GupMKddeaWVenPDQR3OKwt0afXOe5uP6Ks9OXLYrXr0x90CXQ4AAECT0iE+XLdflqKWIV5ZrDbFhDSskUEEqUYqLtyln12arLhwp8orfXp302HtPdawUn5dyiup0J+WVC0wce817ZUSwwITAAAAF1uIw64BsV5l/OchDUppWIulEaQasTCnXT/t21LtmofKaxj68Nuj2pVZFOiy6oW/fpSmnJIKdYwP0+RBDW9MLgAAQGPiPry9Xgw7NIMg1cgF2awa2T1RnRPCZRjSsu8ytP1IYaDLCqiv92br7dRDkqQ5N/eo1dVpAAAA0DTwCbIJsFotGtY1Xt2TImRIWp6WqW8PX9g1Bhqq8kqvHn73O0nS7ZelqG+r6ABXBAAAgIaIINVEWCwWXdM5Tr2SoyRJn+7I0o6jTa9n6h+f7tH+7BLFhTv10IjOgS4HAAAADRRBqgmxWCwa1CFWPVtGSpI+ScvUnqymswDF1kP5ev7zvZKk2Td1U4QrKMAVAQAAoKEiSDUxFotFV3Vsri6J/5szdSCnJNBl1Tm3x6v739oir8/QDT2TNKJ7YqBLAgAAQANGkGqCLBaLhnSJV4e4MHkNQ0u2HtXh/MZ9namnV+zW7qxixYY5NftGrhkFAACAC0OQaqKsFouGd0tQ65gQeXyG3t98RJmF5YEuq05sTM/TP48P6fvrT7qrWagjwBUBAACgoSNINWE2q0XX90hUy6hgVXh9Wrz5sHKK3YEuq1aVVXj1wNtb5DOkn/RuoWHdEgJdEgAAABoBglQTZ7dZdUPPJMVHOFVe6dM7mw4rv7Qi0GXVmtlLtmvfsRI1D3dqxg1dA10OAAAAGgmCFOSwWzWqVwvFhjlUWuHVO5sOq6i8MtBlXbAPtx7V6+vSZbFIc2/tpagQhvQBAACgdhCkIElyBdk0qlcLRQUHqajco3c3HVZphSfQZdXYwdxS/f6drZKku69qpys7xAa4IgAAADQmBCn4hTrt+kmfFgpz2pVXWqnFm4/I7fEGuizTKr0+3fP6JhWVe9QnJUq/Hdox0CUBAACgkSFIoZoIV5Bu7tNCwUE2HSty6/3NR1Tp9QW6LFOe+HinNh/MV4TLrv83preCbPyYAwAAoHbxCROnaBbi0E96t5DDbtWRgnK9v6XhhKl3Nh7SC6v3SZIeG32JkqNDAlwRAAAAGiOCFE6rebhTo3olKchm0aG8Mi3ZelSeeh6mNqbn6ff/960kacrV7XRdj8QAVwQAAIDGKqBBavXq1brhhhuUlJQki8WixYsXV3vcMAw9+uijSkxMVHBwsIYMGaLdu3dXa5Obm6uxY8cqIiJCUVFRmjRpkoqLiy/iUTReiZHBuqlXCwXZLErPLdWSb4/K46ufYepIfpkmv5KqCq9PQ7vG6/6hnQJdEgAAABqxgAapkpIS9ezZU/PmzTvt448//rieeeYZzZ8/X2vXrlVoaKiGDx+u8vJyf5uxY8dq27ZtWr58uZYsWaLVq1dr8uTJF+sQGr0WUcG6qWcL2a0WHcgp1ZKtR+vdML8St0eTX92g7GK3OieE6+mf9ZLVagl0WQAAAGjE7IF88euuu07XXXfdaR8zDENPP/20/vjHP+qmm26SJL3yyiuKj4/X4sWLNWbMGKWlpWnZsmVav369+vXrJ0l69tlnNXLkSD355JNKSkq6aMfSmLVoFqwbeybp/S1HdCCnVIs3HdaNPZPkDLIFujSVVXg16eX1+u5woWJCHXpxfD+FOgP6Yw0AAIAmoN7Okdq/f78yMjI0ZMgQ/7bIyEgNGDBAa9askSStWbNGUVFR/hAlSUOGDJHVatXatWvPuG+3263CwsJqN5xdcnSIRv1gAYr/23hYJe7AXmfK7fFq8qsb9M2+XIU57fr3hEvVshmLSwAAAKDu1dsglZGRIUmKj4+vtj0+Pt7/WEZGhuLi4qo9brfbFR0d7W9zOnPmzFFkZKT/lpycXMvVN04tooL10z4tFeKw6VixW2+nHlJ+aUVAaqnw+DTltY36Yne2goNsWjDxUvVKjgpILQAAAGh66m2QqkvTp09XQUGB/3bw4MFAl9RgNA936pa+LRXhsqugrFJvrD+oAzklF7WGErdHv34tVSvSsuS0W/Xv8f10aevoi1oDAAAAmrZ6G6QSEhIkSZmZmdW2Z2Zm+h9LSEhQVlZWtcc9Ho9yc3P9bU7H6XQqIiKi2g3nLyrEoVv7JSshwiW3x6f3Nh9R6oE8GYZR5699OL9MP52/RivSsuSwW/XPcX11efvYOn9dAAAA4IfqbZBq06aNEhIStHLlSv+2wsJCrV27VgMHDpQkDRw4UPn5+UpNTfW3+fTTT+Xz+TRgwICLXnNTEuq0a3TfFuqaGCFD0pd7svXRtxkqrai7eVMb0/N00z++UtrRQsWGOfT6nZdpcKe4cz8RAAAAqGUBXd6suLhYe/bs8d/fv3+/Nm/erOjoaKWkpOi+++7Tn//8Z3Xo0EFt2rTRI488oqSkJI0aNUqS1KVLF40YMUJ33nmn5s+fr8rKSk2dOlVjxoxhxb6LwG61akiXOMVFOLV61zHtOVasQ/mluqpjc4XWYudUpdenF7/Yr7krdqnC41PnhHC9OL4fC0sAAAAgYAIapDZs2KCrr77af3/atGmSpPHjx2vhwoV66KGHVFJSosmTJys/P19XXnmlli1bJpfL5X/Oa6+9pqlTp+raa6+V1WrV6NGj9cwzz1z0Y2mqLBaLeraMUkKESyvSMpVdXKGPt2UqwWWXPablBe8/9UCeHn73W+3IKJIkDe0ar6d/1oslzgEAABBQAf00Onjw4LPOq7FYLJo9e7Zmz559xjbR0dFatGhRXZQHE+IjXBpzaYpSD+Rp3f5cZZRblTTpOT32Va5+H5un3inNzntfhmFoY3qeXl1zQO9tOSLDkJqFBOmP13fVzX1ayGLhYrsAAAAILP5bH7XGZrWof5totWseqpVbv9fRMqvWHnbrJ899rZ4tIzWoY3Nd2T5WvVOayWGvPj2vrMKr3VlFSj2QpzfXH/T3QEnSLX1bavrILooOdVzsQwIAAABOiyCFWhcT5tTlzT165tF7dfufX9YX6eXacqhAWw4V6NlP98hpt6pZiEOhTpvCnHYVlnv0fU6Jftg56Qqy6seXJGncZa3Uk+tDAQAAoJ4hSKHOeHIO6Z7+UXrs5121atcxfbk7W1/tyVZOSYUyCstPaR8T6lCnhHAN6xqvn/RpqcjgoABUDQAAAJwbQQp1Li7CpVv7JevWfsny+QwdzCtVYZlHxW6PSis8cgXZ1DE+XM3DnYEuFQAAADgvBClcVFarRa1iQgNdBgAAAHBB6u0FeQEAAACgviJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAk+p1kJo5c6YsFku1W+fOnf2Pl5eXa8qUKYqJiVFYWJhGjx6tzMzMAFYMAAAAoCmo10FKkrp166ajR4/6b19++aX/sd/+9rf64IMP9Pbbb+vzzz/XkSNHdPPNNwewWgAAAABNgT3QBZyL3W5XQkLCKdsLCgr073//W4sWLdI111wjSVqwYIG6dOmib775RpdddtkZ9+l2u+V2u/33CwsLa79wAAAAAI1Wve+R2r17t5KSktS2bVuNHTtW6enpkqTU1FRVVlZqyJAh/radO3dWSkqK1qxZc9Z9zpkzR5GRkf5bcnJynR4DAAAAgMalXgepAQMGaOHChVq2bJmef/557d+/Xz/60Y9UVFSkjIwMORwORUVFVXtOfHy8MjIyzrrf6dOnq6CgwH87ePBgHR4FAAAAgMamXg/tu+666/zfX3LJJRowYIBatWqlt956S8HBwTXer9PplNPprI0SAQAAADRB9bpH6mRRUVHq2LGj9uzZo4SEBFVUVCg/P79am8zMzNPOqQIAAACA2tKgglRxcbH27t2rxMRE9e3bV0FBQVq5cqX/8Z07dyo9PV0DBw4MYJUAAAAAGrt6PbTvgQce0A033KBWrVrpyJEjmjFjhmw2m2677TZFRkZq0qRJmjZtmqKjoxUREaF77rlHAwcOPOuKfQAAAABwoep1kDp06JBuu+025eTkqHnz5rryyiv1zTffqHnz5pKkuXPnymq1avTo0XK73Ro+fLiee+65AFcNAAAAoLGr10HqjTfeOOvjLpdL8+bN07x58y5SRQAAAADQwOZIAQAAAEB9QJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAAAAADCJIAUAAAAAJhGkAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACYRpAAAAADAJIIUAAAAAJhEkAIAAAAAkwhSAAAAAGASQQoAAAAATCJIAQAAAIBJBCkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgUqMJUvPmzVPr1q3lcrk0YMAArVu3LtAlAQAAAGikGkWQevPNNzVt2jTNmDFDGzduVM+ePTV8+HBlZWUFujQAAAAAjVCjCFJPPfWU7rzzTk2cOFFdu3bV/PnzFRISopdeeinQpQEAAABohOyBLuBCVVRUKDU1VdOnT/dvs1qtGjJkiNasWXPa57jdbrndbv/9goICSVJhYWHdFnseiouLJUmHdm+Tu6w0wNXU3LFD+yVJqamp/mNqqHbu3Cmp4Z+TzPS9kqSM73dpb2hIgKupOX626h9+tuqXxvJzJTWen63GchyN5XdEajy/J43tZ6u4uLhefB4/UYNhGGdtZzHO1aKeO3LkiFq0aKGvv/5aAwcO9G9/6KGH9Pnnn2vt2rWnPGfmzJmaNWvWxSwTAAAAQANy8OBBtWzZ8oyPN/geqZqYPn26pk2b5r/v8/mUm5urmJgYWSyWAFZW/xQWFio5OVkHDx5UREREoMvBOXC+Gg7OVcPBuWo4OFcNC+er4Whq58owDBUVFSkpKems7Rp8kIqNjZXNZlNmZma17ZmZmUpISDjtc5xOp5xOZ7VtUVFRdVVioxAREdEkfnEaC85Xw8G5ajg4Vw0H56ph4Xw1HE3pXEVGRp6zTYNfbMLhcKhv375auXKlf5vP59PKlSurDfUDAAAAgNrS4HukJGnatGkaP368+vXrp/79++vpp59WSUmJJk6cGOjSAAAAADRCjSJI/exnP9OxY8f06KOPKiMjQ7169dKyZcsUHx8f6NIaPKfTqRkzZpwyFBL1E+er4eBcNRycq4aDc9WwcL4aDs7V6TX4VfsAAAAA4GJr8HOkAAAAAOBiI0gBAAAAgEkEKQAAAAAwiSAFAAAAACYRpHCKv/zlL7r88ssVEhJy3hcqnjBhgiwWS7XbiBEj6rZQ1OhcGYahRx99VImJiQoODtaQIUO0e/fuui0UkqTc3FyNHTtWERERioqK0qRJk1RcXHzW5wwePPiU36277rrrIlXcdMybN0+tW7eWy+XSgAEDtG7durO2f/vtt9W5c2e5XC716NFDH3300UWqFGbO1cKFC0/5/XG5XBex2qZr9erVuuGGG5SUlCSLxaLFixef8zmrVq1Snz595HQ61b59ey1cuLDO60QVs+dr1apVp/xuWSwWZWRkXJyC6wmCFE5RUVGhW265RXfffbep540YMUJHjx71315//fU6qhAn1ORcPf7443rmmWc0f/58rV27VqGhoRo+fLjKy8vrsFJI0tixY7Vt2zYtX75cS5Ys0erVqzV58uRzPu/OO++s9rv1+OOPX4Rqm44333xT06ZN04wZM7Rx40b17NlTw4cPV1ZW1mnbf/3117rttts0adIkbdq0SaNGjdKoUaP03XffXeTKmx6z50qSIiIiqv3+HDhw4CJW3HSVlJSoZ8+emjdv3nm1379/v66//npdffXV2rx5s+677z7dcccd+vjjj+u4Ukjmz9cJO3furPb7FRcXV0cV1lMGcAYLFiwwIiMjz6vt+PHjjZtuuqlO68GZne+58vl8RkJCgvHEE0/4t+Xn5xtOp9N4/fXX67BCbN++3ZBkrF+/3r9t6dKlhsViMQ4fPnzG51111VXGb37zm4tQYdPVv39/Y8qUKf77Xq/XSEpKMubMmXPa9rfeeqtx/fXXV9s2YMAA41e/+lWd1gnz58rM3zHUHUnGu+++e9Y2Dz30kNGtW7dq2372s58Zw4cPr8PKcDrnc74+++wzQ5KRl5d3UWqqr+iRQq1ZtWqV4uLi1KlTJ919993KyckJdEk4yf79+5WRkaEhQ4b4t0VGRmrAgAFas2ZNACtr/NasWaOoqCj169fPv23IkCGyWq1au3btWZ/72muvKTY2Vt27d9f06dNVWlpa1+U2GRUVFUpNTa32O2G1WjVkyJAz/k6sWbOmWntJGj58OL9Ddawm50qSiouL1apVKyUnJ+umm27Stm3bLka5MInfq4apV69eSkxM1NChQ/XVV18FupyLzh7oAtA4jBgxQjfffLPatGmjvXv36g9/+IOuu+46rVmzRjabLdDl4bgTY5fj4+OrbY+Pj29y45ovtoyMjFOGPNjtdkVHR5/1vf/5z3+uVq1aKSkpSVu3btXvfvc77dy5U++8805dl9wkZGdny+v1nvZ3YseOHad9TkZGBr9DAVCTc9WpUye99NJLuuSSS1RQUKAnn3xSl19+ubZt26aWLVtejLJxns70e1VYWKiysjIFBwcHqDKcTmJioubPn69+/frJ7XbrxRdf1ODBg7V27Vr16dMn0OVdNASpJuL3v/+9HnvssbO2SUtLU+fOnWu0/zFjxvi/79Gjhy655BK1a9dOq1at0rXXXlujfTZVdX2uULvO93zV1A/nUPXo0UOJiYm69tprtXfvXrVr167G+wWagoEDB2rgwIH++5dffrm6dOmif/7zn/rTn/4UwMqAhq1Tp07q1KmT//7ll1+uvXv3au7cuXr11VcDWNnFRZBqIu6//35NmDDhrG3atm1ba6/Xtm1bxcbGas+ePQQpk+ryXCUkJEiSMjMzlZiY6N+emZmpXr161WifTd35nq+EhIRTJsR7PB7l5ub6z8v5GDBggCRpz549BKlaEBsbK5vNpszMzGrbMzMzz3heEhISTLVH7ajJuTpZUFCQevfurT179tRFibgAZ/q9ioiIoDeqgejfv7++/PLLQJdxURGkmojmzZurefPmF+31Dh06pJycnGof1nF+6vJctWnTRgkJCVq5cqU/OBUWFmrt2rWmV2lElfM9XwMHDlR+fr5SU1PVt29fSdKnn34qn8/nD0fnY/PmzZLE71YtcTgc6tu3r1auXKlRo0ZJknw+n1auXKmpU6ee9jkDBw7UypUrdd999/m3LV++vFrPB2pfTc7Vybxer7799luNHDmyDitFTQwcOPCUywjwe9WwbN68uen9bQr0aheofw4cOGBs2rTJmDVrlhEWFmZs2rTJ2LRpk1FUVORv06lTJ+Odd94xDMMwioqKjAceeMBYs2aNsX//fmPFihVGnz59jA4dOhjl5eWBOowmwey5MgzD+Nvf/mZERUUZ7733nrF161bjpptuMtq0aWOUlZUF4hCalBEjRhi9e/c21q5da3z55ZdGhw4djNtuu83/+KFDh4xOnToZa9euNQzDMPbs2WPMnj3b2LBhg7F//37jvffeM9q2bWsMGjQoUIfQKL3xxhuG0+k0Fi5caGzfvt2YPHmyERUVZWRkZBiGYRjjxo0zfv/73/vbf/XVV4bdbjeefPJJIy0tzZgxY4YRFBRkfPvtt4E6hCbD7LmaNWuW8fHHHxt79+41UlNTjTFjxhgul8vYtm1boA6hySgqKvL/TZJkPPXUU8amTZuMAwcOGIZhGL///e+NcePG+dvv27fPCAkJMR588EEjLS3NmDdvnmGz2Yxly5YF6hCaFLPna+7cucbixYuN3bt3G99++63xm9/8xrBarcaKFSsCdQgBQZDCKcaPH29IOuX22Wef+dtIMhYsWGAYhmGUlpYaw4YNM5o3b24EBQUZrVq1Mu68807/HzbUHbPnyjCqlkB/5JFHjPj4eMPpdBrXXnutsXPnzotffBOUk5Nj3HbbbUZYWJgRERFhTJw4sVro3b9/f7Xzl56ebgwaNMiIjo42nE6n0b59e+PBBx80CgoKAnQEjdezzz5rpKSkGA6Hw+jfv7/xzTff+B+76qqrjPHjx1dr/9ZbbxkdO3Y0HA6H0a1bN+PDDz+8yBU3XWbO1X333edvGx8fb4wcOdLYuHFjAKpuek4sj33y7cT5GT9+vHHVVVed8pxevXoZDofDaNu2bbW/XahbZs/XY489ZrRr185wuVxGdHS0MXjwYOPTTz8NTPEBZDEMw7ho3V8AAAAA0AhwHSkAAAAAMIkgBQAAAAAmEaQAAAAAwCSCFAAAAACYRJACAAAAAJMIUgAAAABgEkEKAAAAAEwiSAEAAACASQQpAADq2MKFCxUVFRXoMgAAtYggBQCot44dO6a7775bKSkpcjqdSkhI0PDhw/XVV19JkiwWixYvXhzYIk/SunVrPf3004EuAwBQx+yBLgAAgDMZPXq0Kioq9PLLL6tt27bKzMzUypUrlZOTc977qKiokMPhqMMqAQBNET1SAIB6KT8/X1988YUee+wxXX311WrVqpX69++v6dOn68Ybb1Tr1q0lST/5yU9ksVj892fOnKlevXrpxRdfVJs2beRyufz7u+OOO9S8eXNFRETommuu0ZYtW/yvd+J5r776qlq3bq3IyEiNGTNGRUVF/jZFRUUaO3asQkNDlZiYqLlz52rw4MG67777JEmDBw/WgQMH9Nvf/lYWi0UWi6XaMX388cfq0qWLwsLCNGLECB09erTu3kAAQJ0iSAEA6qWwsDCFhYVp8eLFcrvdpzy+fv16SdKCBQt09OhR/31J2rNnj/7v//5P77zzjjZv3ixJuuWWW5SVlaWlS5cqNTVVffr00bXXXqvc3Fz/8/bu3avFixdryZIlWrJkiT7//HP97W9/8z8+bdo0ffXVV3r//fe1fPlyffHFF9q4caP/8XfeeUctW7bU7NmzdfTo0WpBqbS0VE8++aReffVVrV69Wunp6XrggQdq7f0CAFxcDO0DANRLdrtdCxcu1J133qn58+erT58+uuqqqzRmzBhdcsklat68uSQpKipKCQkJ1Z5bUVGhV155xd/myy+/1Lp165SVlSWn0ylJevLJJ7V48WL997//1eTJkyVJPp9PCxcuVHh4uCRp3LhxWrlypf7yl7+oqKhIL7/8shYtWqRrr71WUlWIS0pK8r9udHS0bDabwsPDT6mpsrJS8+fPV7t27SRJU6dO1ezZs2v7bQMAXCT0SAEA6q3Ro0fryJEjev/99zVixAitWrVKffr00cKFC8/6vFatWvlDlCRt2bJFxcXFiomJ8fd0hYWFaf/+/dq7d6+/XevWrf0hSpISExOVlZUlSdq3b58qKyvVv39//+ORkZHq1KnTeR1LSEiIP0SdvG8AQMNDjxQAoF5zuVwaOnSohg4dqkceeUR33HGHZsyYoQkTJpzxOaGhodXuFxcXKzExUatWrTql7Q+XJQ8KCqr2mMVikc/nu5Dyz7pvwzBqZd8AgIuPHikAQIPStWtXlZSUSKoKJ16v95zP6dOnjzIyMmS329W+fftqt9jY2PN63bZt2yooKKjaXKyCggLt2rWrWjuHw3FeNQEAGjaCFACgXsrJydE111yj//znP9q6dav279+vt99+W48//rhuuukmSVVD8VauXKmMjAzl5eWdcV9DhgzRwIEDNWrUKH3yySf6/vvv9fXXX+vhhx/Whg0bzque8PBwjR8/Xg8++KA+++wzbdu2TZMmTZLVaq22Ol/r1q21evVqHT58WNnZ2Rf2JgAA6i2CFACgXgoLC9OAAQM0d+5cDRo0SN27d9cjjzyiO++8U//4xz8kSX//+9+1fPlyJScnq3fv3mfcl8Vi0UcffaRBgwZp4sSJ6tixo8aMGaMDBw4oPj7+vGt66qmnNHDgQP34xz/WkCFDdMUVV6hLly7+JdYlafbs2fr+++/Vrl27avO0AACNi8VggDYAADVSUlKiFi1a6O9//7smTZoU6HIAABcRi00AAHCeNm3apB07dqh///4qKCjwL19+YqghAKDpIEgBAGDCk08+qZ07d8rhcKhv37764osvznvBCgBA48HQPgAAAAAwicUmAAAAAMAkghQAAAAAmESQAgAAAACTCFIAAAAAYBJBCgAAAABMIkgBAAAAgEkEKQAAAAAwiSAFAAAAACb9f1MPhpvSCf1EAAAAAElFTkSuQmCC"},"metadata":{}},{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Pairplot\nsns.pairplot(df[['Strength', 'Speed', 'Intelligence']])\nplt.suptitle(\"Pairplot of Strength, Speed, and Intelligence\", y=1.02)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:01.428458Z","iopub.execute_input":"2024-07-21T17:50:01.428819Z","iopub.status.idle":"2024-07-21T17:50:03.849306Z","shell.execute_reply.started":"2024-07-21T17:50:01.428786Z","shell.execute_reply":"2024-07-21T17:50:03.847992Z"},"trusted":true},"execution_count":64,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n with pd.option_context('mode.use_inf_as_na', True):\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Heatmap\nplt.figure(figsize=(10, 6))\nsns.heatmap(df[['Strength', 'Speed', 'Intelligence']].corr(), annot=True, cmap='coolwarm')\nplt.title(\"Heatmap of Correlation between Strength, Speed, and Intelligence\")\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:03.850773Z","iopub.execute_input":"2024-07-21T17:50:03.851171Z","iopub.status.idle":"2024-07-21T17:50:04.190567Z","shell.execute_reply.started":"2024-07-21T17:50:03.851138Z","shell.execute_reply":"2024-07-21T17:50:04.189281Z"},"trusted":true},"execution_count":65,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Character distribution by Universe\nplt.figure(figsize=(8, 6))\ndf['Universe'].value_counts().plot(kind='bar', color=['blue', 'red'])\nplt.title('Character Distribution by Universe')\nplt.xlabel('Universe')\nplt.ylabel('Count')\nplt.xticks(ticks=[0, 1], labels=['Marvel', 'DC Comics'], rotation=0)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:04.191984Z","iopub.execute_input":"2024-07-21T17:50:04.192376Z","iopub.status.idle":"2024-07-21T17:50:04.412246Z","shell.execute_reply.started":"2024-07-21T17:50:04.192343Z","shell.execute_reply":"2024-07-21T17:50:04.411012Z"},"trusted":true},"execution_count":66,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Average Strength by Universe\nplt.figure(figsize=(8, 6))\nsns.barplot(x='Universe', y='Strength', data=df, estimator=np.mean, palette='coolwarm')\nplt.title('Average Strength by Universe')\nplt.xlabel('Universe')\nplt.ylabel('Average Strength')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:04.413981Z","iopub.execute_input":"2024-07-21T17:50:04.414485Z","iopub.status.idle":"2024-07-21T17:50:04.689671Z","shell.execute_reply.started":"2024-07-21T17:50:04.414444Z","shell.execute_reply":"2024-07-21T17:50:04.688552Z"},"trusted":true},"execution_count":67,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Special Abilities Distribution\nplt.figure(figsize=(10, 6))\ndf['SpecialAbilities'].value_counts().plot(kind='barh', color='green')\nplt.title('Special Abilities Distribution')\nplt.xlabel('Count')\nplt.ylabel('Special Abilities')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:04.691104Z","iopub.execute_input":"2024-07-21T17:50:04.691531Z","iopub.status.idle":"2024-07-21T17:50:04.949388Z","shell.execute_reply.started":"2024-07-21T17:50:04.691485Z","shell.execute_reply":"2024-07-21T17:50:04.948123Z"},"trusted":true},"execution_count":68,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Battle Outcome Distribution\nplt.figure(figsize=(6, 4))\ndf['BattleOutcome'].value_counts().plot(kind='pie', autopct='%1.2f%%', colors=['skyblue', 'lightcoral'])\nplt.title('Battle Outcome Distribution')\nplt.ylabel('')\nplt.legend(['Character 1 wins', 'Character 2 wins'], loc='best')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:04.950747Z","iopub.execute_input":"2024-07-21T17:50:04.951112Z","iopub.status.idle":"2024-07-21T17:50:05.119985Z","shell.execute_reply.started":"2024-07-21T17:50:04.951084Z","shell.execute_reply":"2024-07-21T17:50:05.118666Z"},"trusted":true},"execution_count":69,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Encode categorical variables\nle = LabelEncoder()\ndf['Character'] = le.fit_transform(df['Character'])\ndf['Universe'] = le.fit_transform(df['Universe'])\ndf['SpecialAbilities'] = le.fit_transform(df['SpecialAbilities'])\ndf['Weaknesses'] = le.fit_transform(df['Weaknesses'])","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:05.122021Z","iopub.execute_input":"2024-07-21T17:50:05.123387Z","iopub.status.idle":"2024-07-21T17:50:05.139400Z","shell.execute_reply.started":"2024-07-21T17:50:05.123309Z","shell.execute_reply":"2024-07-21T17:50:05.138020Z"},"trusted":true},"execution_count":70,"outputs":[]},{"cell_type":"code","source":"# Split data into train and test sets\nX = df.drop('BattleOutcome', axis=1)\ny = df['BattleOutcome']\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:05.141184Z","iopub.execute_input":"2024-07-21T17:50:05.142276Z","iopub.status.idle":"2024-07-21T17:50:05.155740Z","shell.execute_reply.started":"2024-07-21T17:50:05.142223Z","shell.execute_reply":"2024-07-21T17:50:05.154327Z"},"trusted":true},"execution_count":71,"outputs":[]},{"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier, ExtraTreesClassifier, BaggingClassifier\nfrom sklearn.svm import SVC\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom xgboost import XGBClassifier\nfrom catboost import CatBoostClassifier\n# Define classifier models\nmodels = {\n 'Random Forest': RandomForestClassifier(),\n 'Support Vector Classifier': SVC(),\n 'Logistic Regression': LogisticRegression(),\n 'Decision Tree': DecisionTreeClassifier(),\n 'K-Nearest Neighbors': KNeighborsClassifier(),\n 'Gradient Boosting': GradientBoostingClassifier(),\n 'AdaBoost': AdaBoostClassifier(),\n 'CatBoost': CatBoostClassifier(),\n 'Extra Trees': ExtraTreesClassifier(),\n 'XGBoost': XGBClassifier(),\n 'Bagging Classifier': BaggingClassifier()\n}\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:05.157833Z","iopub.execute_input":"2024-07-21T17:50:05.158732Z","iopub.status.idle":"2024-07-21T17:50:05.173619Z","shell.execute_reply.started":"2024-07-21T17:50:05.158680Z","shell.execute_reply":"2024-07-21T17:50:05.172311Z"},"trusted":true},"execution_count":72,"outputs":[]},{"cell_type":"code","source":"import pandas as pd\nfrom sklearn.metrics import accuracy_score, classification_report, confusion_matrix, ConfusionMatrixDisplay\nimport matplotlib.pyplot as plt\n# Initialize a DataFrame to store evaluation results\nresults = pd.DataFrame(columns=['Model', 'Accuracy', 'Precision', 'Recall', 'F1 Score'])\n# Train and evaluate models\nevaluation_results = []\nfor model_name, model in models.items():\n model.fit(X_train, y_train)\n y_pred = model.predict(X_test)\n # Calculate evaluation metrics\n accuracy = accuracy_score(y_test, y_pred)\n report = classification_report(y_test, y_pred, output_dict=True)\n precision = report['macro avg']['precision']\n recall = report['macro avg']['recall']\n f1_score = report['macro avg']['f1-score']\n # Append results to list\n evaluation_results.append({\n 'Model': model_name,\n 'Accuracy': accuracy,\n 'Precision': precision,\n 'Recall': recall,\n 'F1 Score': f1_score\n })\n # Display confusion matrix\n cm = confusion_matrix(y_test, y_pred)\n disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n disp.plot()\n plt.title(f\"Confusion Matrix for {model_name}\")\n plt.show()\n# Create DataFrame from evaluation results\nresults = pd.DataFrame(evaluation_results)\n# Save results to CSV\nresults.to_csv('evaluation_results.csv', index=False)\n# Display evaluation results in table form\nprint(results)\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:05.175748Z","iopub.execute_input":"2024-07-21T17:50:05.176114Z","iopub.status.idle":"2024-07-21T17:50:10.785018Z","shell.execute_reply.started":"2024-07-21T17:50:05.176083Z","shell.execute_reply":"2024-07-21T17:50:10.783820Z"},"trusted":true},"execution_count":73,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"iVBORw0KGgoAAAANSUhEUgAAAfsAAAHHCAYAAAC4M/EEAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABFVUlEQVR4nO3deVhUZf8/8PewzLAOiAojiYA7uIs+ROaWhFulaV/TrJBcysByzbRUQItfWrlvlYkalrZoj6Ymau5kiVK5kShuIWCiICDbzP37g4epEdAZZmCcOe/XdZ3rcu5zn3M+M4x8uJdzH5kQQoCIiIislo25AyAiIqLaxWRPRERk5ZjsiYiIrByTPRERkZVjsiciIrJyTPZERERWjsmeiIjIyjHZExERWTkmeyIiIivHZE8GO3/+PMLCwuDm5gaZTIatW7ea9PyXLl2CTCZDfHy8Sc9ryXr16oVevXqZ7Hz5+fkYM2YMVCoVZDIZJk6caLJz1xY/Pz+MGjXK3GEQWSQmewt14cIFvPrqq2jatCkcHBygVCrRrVs3LF68GHfv3q3Va4eHh+OPP/7Ae++9hw0bNqBLly61er26NGrUKMhkMiiVyio/x/Pnz0Mmk0Emk+HDDz80+PwZGRmIjo5GSkqKCaKtuffffx/x8fEYP348NmzYgJdeeqlOrqtWq+Ht7Q2ZTIadO3fWyTUr/nj896ZUKtGxY0csW7YMarW6TuK4nxUrVvCPW6pVduYOgAz3ww8/4P/+7/+gUCjw8ssvo23btigpKcHhw4cxbdo0nD59Gp988kmtXPvu3btISkrCO++8g6ioqFq5hq+vL+7evQt7e/taOf+D2NnZobCwENu2bcOwYcN09iUkJMDBwQFFRUU1OndGRgZiYmLg5+eHjh076n3c7t27a3S96uzbtw+PPvoo5syZY9Lz6nPd69evw8/PDwkJCejfv3+dXXvEiBEYMGAAACA3Nxc7duzAhAkTcPnyZSxYsKDO4qjKihUr0KBBA/ZcUK1hsrcw6enpGD58OHx9fbFv3z40atRIuy8yMhJpaWn44Ycfau36N27cAAC4u7vX2jVkMhkcHBxq7fwPolAo0K1bN3z55ZeVkv3GjRsxcOBAfPvtt3USS2FhIZycnCCXy0163uzsbAQGBprsfGVlZdBoNA+M84svvkDnzp0RHh6OmTNnoqCgAM7OziaL4346d+6MF198Ufv69ddfR3BwMDZu3Gj2ZE9U29iNb2Hmz5+P/Px8rFmzRifRV2jevDnefPNN7euysjLMnTsXzZo1g0KhgJ+fH2bOnIni4mKd4/z8/PDUU0/h8OHD+M9//gMHBwc0bdoU69ev19aJjo6Gr68vAGDatGmQyWTw8/MDUN79XfHvf4uOjoZMJtMpS0xMxOOPPw53d3e4uLigVatWmDlzpnZ/dWP2+/btQ/fu3eHs7Ax3d3cMGjQIZ8+erfJ6aWlpGDVqFNzd3eHm5oaIiAgUFhZW/8He44UXXsDOnTtx+/Ztbdmvv/6K8+fP44UXXqhUPycnB1OnTkW7du3g4uICpVKJ/v3747ffftPW2b9/P7p27QoAiIiI0HYpV7zPXr16oW3btkhOTkaPHj3g5OSk/VzuHbMPDw+Hg4NDpffft29f1KtXDxkZGVW+r/3790MmkyE9PR0//PCDNoZLly4BKP8jYPTo0fDy8oKDgwM6dOiAdevW6Zyj4ufz4YcfYtGiRdrv1pkzZ+77md69exdbtmzB8OHDMWzYMNy9exfff/99pXpCCMybNw+NGzeGk5MTevfujdOnT9foM78fmUwGLy8v2NlVbvOsWLECbdq0gUKhgLe3NyIjI3W+CxW+/vprBAUFwdHREQ0aNMCLL76Iv/76S6dOZmYmIiIi0LhxYygUCjRq1AiDBg3SfuZ+fn44ffo0Dhw4oP15mHJ+BhHAlr3F2bZtG5o2bYrHHntMr/pjxozBunXr8Nxzz2HKlCk4duwY4uLicPbsWWzZskWnblpaGp577jmMHj0a4eHh+PzzzzFq1CgEBQWhTZs2GDJkCNzd3TFp0iRtl6iLi4tB8Z8+fRpPPfUU2rdvj9jYWCgUCqSlpeHIkSP3PW7Pnj3o378/mjZtiujoaNy9exdLly5Ft27dcOLEiUp/aAwbNgz+/v6Ii4vDiRMn8Nlnn8HT0xMffPCBXnEOGTIEr732Gr777ju88sorAMpb9a1bt0bnzp0r1b948SK2bt2K//u//4O/vz+ysrKwevVq9OzZE2fOnIG3tzcCAgIQGxuL2bNnY9y4cejevTsA6Pwsb968if79+2P48OF48cUX4eXlVWV8ixcvxr59+xAeHo6kpCTY2tpi9erV2L17NzZs2ABvb+8qjwsICMCGDRswadIkNG7cGFOmTAEANGzYEHfv3kWvXr2QlpaGqKgo+Pv74+uvv8aoUaNw+/ZtnT8iAWDt2rUoKirCuHHjoFAo4OHhcd/P9L///S/y8/MxfPhwqFQq9OrVCwkJCZX+eJo9ezbmzZuHAQMGYMCAAThx4gTCwsJQUlJi8Gf+b4WFhfj7778BAHl5edi5cyd27dqFGTNm6NSLjo5GTEwMQkNDMX78eKSmpmLlypX49ddfceTIEe3wUnx8PCIiItC1a1fExcUhKysLixcvxpEjR3Dy5Elt79fQoUNx+vRpTJgwAX5+fsjOzkZiYiKuXLkCPz8/LFq0CBMmTICLiwveeecdAKj2505UY4IsRm5urgAgBg0apFf9lJQUAUCMGTNGp3zq1KkCgNi3b5+2zNfXVwAQBw8e1JZlZ2cLhUIhpkyZoi1LT08XAMSCBQt0zhkeHi58fX0rxTBnzhzx76/ZwoULBQBx48aNauOuuMbatWu1ZR07dhSenp7i5s2b2rLffvtN2NjYiJdffrnS9V555RWdcz777LOifv361V7z3+/D2dlZCCHEc889J/r06SOEEEKtVguVSiViYmKq/AyKioqEWq2u9D4UCoWIjY3Vlv3666+V3luFnj17CgBi1apVVe7r2bOnTtmPP/4oAIh58+aJixcvChcXFzF48OAHvkchyn/eAwcO1ClbtGiRACC++OILbVlJSYkICQkRLi4uIi8vT/u+AAilUimys7P1up4QQjz11FOiW7du2teffPKJsLOz0zlHdna2kMvlYuDAgUKj0WjLZ86cKQCI8PBwbZm+n3lFvFVt48eP17lOxfXDwsJ0zr1s2TIBQHz++efaz8XT01O0bdtW3L17V1tv+/btAoCYPXu2EEKIW7duVfn/5V5t2rSp9PMlMiV241uQvLw8AICrq6te9Xfs2AEAmDx5sk55RWvu3rH9wMBAbWsTKG/ttWrVChcvXqxxzPeqaO18//330Gg0eh1z/fp1pKSkYNSoUTqtx/bt2+PJJ5/Uvs9/e+2113Red+/eHTdv3tR+hvp44YUXsH//fmRmZmLfvn3IzMyssgsfKB/nt7Ep/++kVqtx8+ZN7RDFiRMn9L6mQqFARESEXnXDwsLw6quvIjY2FkOGDIGDgwNWr16t97XutWPHDqhUKowYMUJbZm9vjzfeeAP5+fk4cOCATv2hQ4eiYcOGep375s2b+PHHH3XOPXToUMhkMmzevFlbtmfPHpSUlGDChAk6wz9V3Rpo6Gc+btw4JCYmIjExEd9++y0iIyOxevVqnf8fFdefOHGi9twAMHbsWCiVSu3/mePHjyM7Oxuvv/66zvySgQMHonXr1tp6jo6OkMvl2L9/P27duqXXZ0VUG5jsLYhSqQQA3LlzR6/6ly9fho2NDZo3b65TrlKp4O7ujsuXL+uUN2nSpNI56tWrZ9JfUs8//zy6deuGMWPGwMvLC8OHD8fmzZvvm/gr4mzVqlWlfQEBAfj7779RUFCgU37ve6lXrx4AGPReBgwYAFdXV2zatAkJCQno2rVrpc+ygkajwcKFC9GiRQsoFAo0aNAADRs2xO+//47c3Fy9r/nII48YNBnvww8/hIeHB1JSUrBkyRJ4enrqfey9Ll++jBYtWugkOaD8M67Y/2/+/v56n3vTpk0oLS1Fp06dkJaWhrS0NOTk5CA4OBgJCQk6MQBAixYtdI5v2LCh9mdYwdDPvEWLFggNDUVoaCiGDBmCZcuW4fXXX8eiRYvwxx9/6Fz/3u+aXC5H06ZNtfvv951s3bq1dr9CocAHH3yAnTt3wsvLCz169MD8+fORmZmp92dHZApM9hZEqVTC29sbp06dMui4eyfIVcfW1rbKciFEja9x7z3Mjo6OOHjwIPbs2YOXXnoJv//+O55//nk8+eSTJr3f2Zj3UkGhUGDIkCFYt24dtmzZUm2rHii/b33y5Mno0aMHvvjiC/z4449ITExEmzZt9O7BAMo/H0OcPHkS2dnZAKBNWHXFkFgrEnq3bt3QokUL7Xb48GEkJSXVqPfIFJ95nz59AAAHDx40+Pr6mjhxIv7880/ExcXBwcEBs2bNQkBAAE6ePFlr1yS6F5O9hXnqqadw4cIFJCUlPbCur68vNBoNzp8/r1OelZWF27dva2fWm0K9evWqnK18b2sQAGxsbNCnTx98/PHHOHPmDN577z3s27cPP/30U5XnrogzNTW10r5z586hQYMGtXb71gsvvICTJ0/izp07GD58eLX1vvnmG/Tu3Rtr1qzB8OHDERYWhtDQ0Eqfib5/eOmjoKAAERERCAwMxLhx4zB//nz8+uuvNT6fr68vzp8/XylRnjt3Tru/JtLT03H06FFERUXh66+/1tk2bdoEuVyOjRs36lzj3u/sjRs3KvXK6PuZ309ZWRmA8hUF/339e79rJSUlSE9P1+6/33cyNTW10mfVrFkzTJkyBbt378apU6dQUlKCjz76SLvflN8Loqow2VuYt956C87OzhgzZgyysrIq7b9w4QIWL14MANoFRBYtWqRT5+OPPwZQPr5oKs2aNUNubi5+//13bdn169crzfjPycmpdGzF4jL33g5YoVGjRujYsSPWrVun84v81KlT2L17t/Z91obevXtj7ty5WLZsGVQqVbX1bG1tK/UafP3115Vuw6r4o8SQhFSd6dOn48qVK1i3bh0+/vhj+Pn5ITw8vNrP8UEGDBiAzMxMbNq0SVtWVlaGpUuXwsXFBT179qzReSta9W+99Raee+45nW3YsGHo2bOntk5oaCjs7e2xdOlSnc/z3u8woP9nfj/btm0DAHTo0EF7fblcjiVLluice82aNcjNzdX+n+nSpQs8PT2xatUqnc97586dOHv2rLZeYWFhpQWYmjVrBldXV53jnJ2dTfKdIKoOb72zMM2aNcPGjRvx/PPPIyAgQGcFvaNHj2pvlQLKf4GFh4fjk08+we3bt9GzZ0/88ssvWLduHQYPHozevXubLK7hw4dj+vTpePbZZ/HGG2+gsLAQK1euRMuWLXUmS8XGxuLgwYMYOHAgfH19kZ2djRUrVqBx48Z4/PHHqz3/ggUL0L9/f4SEhGD06NHaW+/c3NwQHR1tsvdxLxsbG7z77rsPrPfUU08hNjYWEREReOyxx/DHH38gISEBTZs21anXrFkzuLu7Y9WqVXB1dYWzszOCg4MNGv8GytccWLFiBebMmaO9FXDt2rXo1asXZs2ahfnz5xt0PqB8Atvq1asxatQoJCcnw8/PD9988w2OHDmCRYsW6T0x9F4JCQno2LEjfHx8qtz/zDPPYMKECThx4gQ6d+6MqVOnIi4uDk899RQGDBiAkydPYufOnWjQoIHOcfp+5hVOnDiBL774AkD5vJe9e/fi22+/xWOPPYawsDAA5XMDZsyYgZiYGPTr1w/PPPMMUlNTsWLFCnTt2lW7KI+9vT0++OADREREoGfPnhgxYoT21js/Pz9MmjQJAPDnn3+iT58+GDZsGAIDA2FnZ4ctW7YgKytLp6coKCgIK1euxLx589C8eXN4enriiSeeqNHnTVQlc94KQDX3559/irFjxwo/Pz8hl8uFq6ur6Natm1i6dKkoKirS1istLRUxMTHC399f2NvbCx8fHzFjxgydOkJUfSuWEJVv+aru1jshhNi9e7do27atkMvlolWrVuKLL76odOvd3r17xaBBg4S3t7eQy+XC29tbjBgxQvz555+VrnHv7Wl79uwR3bp1E46OjkKpVIqnn35anDlzRqdOxfXuvbVv7dq1AoBIT0+v9jMVQvfWu+pUd+vdlClTRKNGjYSjo6Po1q2bSEpKqvKWue+//14EBgYKOzs7nffZs2dP0aZNmyqv+e/z5OXlCV9fX9G5c2dRWlqqU2/SpEnCxsZGJCUl3fc9VPfzzsrKEhEREaJBgwZCLpeLdu3aVfo53O87cK/k5GQBQMyaNavaOpcuXRIAxKRJk4QQ5bc5xsTEaD/LXr16iVOnTglfX99Kt97p85lXdeudnZ2daNq0qZg2bZq4c+dOpZiWLVsmWrduLezt7YWXl5cYP368uHXrVqV6mzZtEp06dRIKhUJ4eHiIkSNHimvXrmn3//333yIyMlK0bt1aODs7Czc3NxEcHCw2b96sc57MzEwxcOBA4erqKgDwNjwyOZkQBsxYIiIiIovDMXsiIiIrx2RPRERk5ZjsiYiIrByTPRERkZVjsiciIrJyTPZERERWzqIX1dFoNMjIyICrqyuXmyQiskBCCNy5cwfe3t6VHsJkSkVFRSgpKTH6PHK5XOdJh5bCopN9RkZGtatyERGR5bh69SoaN25cK+cuKiqCv68LMrONf9iWSqVCenq6xSV8i072Fct3Xj7hB6ULRyTIOj3bsp25QyCqNWUoxWHsqPFyzPooKSlBZrYal5P9oHStea7Iu6OBb9AllJSUMNnXpYque6WLjVE/QKKHmZ3M3twhENWe/63hWhdDsS6uMri41vw6GljucLFFJ3siIiJ9qYUGaiMWiFcLzYMrPaSY7ImISBI0ENCg5tnemGPNjX3fREREVo4teyIikgQNNDCmI964o82LyZ6IiCRBLQTURjzV3ZhjzY3d+ERERFaOLXsiIpIEKU/QY7InIiJJ0EBALdFkz258IiIiK8eWPRERSQK78YmIiKwcZ+MTERGR1WLLnoiIJEHzv82Y4y0Vkz0REUmC2sjZ+MYca25M9kREJAlqASOfeme6WOoax+yJiIisHFv2REQkCRyzJyIisnIayKCGzKjjLRW78YmIiKwcW/ZERCQJGlG+GXO8pWKyJyIiSVAb2Y1vzLHmxm58IiIiK8eWPRERSYKUW/ZM9kREJAkaIYNGGDEb34hjzY3d+ERERFaOLXsiIpIEduMTERFZOTVsoDaiQ1ttwljqGpM9ERFJgjByzF5wzJ6IiIgeVmzZExGRJHDMnoiIyMqphQ3UwogxewteLpfd+ERERFaOLXsiIpIEDWTQGNHG1cBym/ZM9kREJAlSHrNnNz4REZGVY8ueiIgkwfgJeuzGJyIieqiVj9kb8SAcduMTERHRw4oteyIikgSNkWvjczY+ERHRQ45j9kRERFZOAxvJ3mfPMXsiIiIrx5Y9ERFJglrIoDbiMbXGHGtuTPZERCQJaiMn6KnZjU9EREQPK7bsiYhIEjTCBhojZuNrOBufiIjo4cZufCIiIrJabNkTEZEkaGDcjHqN6UKpc0z2REQkCcYvqmO5neGWGzkRERHphS17IiKSBOPXxrfc9jGTPRERSYKUn2fPZE9ERJIg5Za95UZOREREemHLnoiIJMH4RXUst33MZE9ERJKgETJojLnP3oKfeme5f6YQERGRXtiyJyIiSdAY2Y3PRXWIiIgechVPvTNmM0RcXBy6du0KV1dXeHp6YvDgwUhNTdWp06tXL8hkMp3ttdde06lz5coVDBw4EE5OTvD09MS0adNQVlZmUCxs2RMREdWCAwcOIDIyEl27dkVZWRlmzpyJsLAwnDlzBs7Oztp6Y8eORWxsrPa1k5OT9t9qtRoDBw6ESqXC0aNHcf36dbz88suwt7fH+++/r3csTPZERCQJasigNmJhHEOP3bVrl87r+Ph4eHp6Ijk5GT169NCWOzk5QaVSVXmO3bt348yZM9izZw+8vLzQsWNHzJ07F9OnT0d0dDTkcrlesbAbn4iIJMFU3fh5eXk6W3FxsV7Xz83NBQB4eHjolCckJKBBgwZo27YtZsyYgcLCQu2+pKQktGvXDl5eXtqyvn37Ii8vD6dPn9b7vbNlT0REZAAfHx+d13PmzEF0dPR9j9FoNJg4cSK6deuGtm3bastfeOEF+Pr6wtvbG7///jumT5+O1NRUfPfddwCAzMxMnUQPQPs6MzNT75iZ7ImISBLUMLwr/t7jAeDq1atQKpXacoVC8cBjIyMjcerUKRw+fFinfNy4cdp/t2vXDo0aNUKfPn1w4cIFNGvWrMax3ovd+EREJAmm6sZXKpU624OSfVRUFLZv346ffvoJjRs3vm/d4OBgAEBaWhoAQKVSISsrS6dOxevqxvmrwmRPRESSUPEgHGM2QwghEBUVhS1btmDfvn3w9/d/4DEpKSkAgEaNGgEAQkJC8McffyA7O1tbJzExEUqlEoGBgXrHwm58IiKiWhAZGYmNGzfi+++/h6urq3aM3c3NDY6Ojrhw4QI2btyIAQMGoH79+vj9998xadIk9OjRA+3btwcAhIWFITAwEC+99BLmz5+PzMxMvPvuu4iMjNRr+KACkz0REUmCMPJ59sLAY1euXAmgfOGcf1u7di1GjRoFuVyOPXv2YNGiRSgoKICPjw+GDh2Kd999V1vX1tYW27dvx/jx4xESEgJnZ2eEh4fr3JevDyZ7IiKShLp+nr0Q4r77fXx8cODAgQeex9fXFzt27DDo2vfimD0REZGVY8ueiIgkQcqPuGWyJyIiSVAb+dQ7Y441N8uNnIiIiPTClj0REUkCu/GJiIisnAY20BjRoW3MseZmuZETERGRXtiyJyIiSVALGdRGdMUbc6y5MdkTEZEkcMyeiIjIyol/PbmupsdbKsuNnIiIiPTClj0REUmCGjKojXgQjjHHmhuTPRERSYJGGDfurrn/c20eauzGJyIisnJs2UvcV0s9cWSHO66mKSB30CCwSyFGv5MBn+bF2joZl+T4NNYbp39xQWmJDEG98xA57y/Ua1imrfPyfwKRdU2uc+5XZmTg+QnZdfZeiGpiWFQWRs/MxJZPG2DVnEfu2Ssw74t0dH3iDqJf8UPSLjezxEimoTFygp4xx5rbQxH58uXL4efnBwcHBwQHB+OXX34xd0iS8XuSC54e9TcWbT+PuK8uQF0GzBzRDEWF5V+NokIbzBzRDDIZ8MHXafj4+/MoK7HB7HB/aDS653p52nV8mXJKuw0a/bcZ3hGR/lp2KMTAF3Nw8bRDlfufHfs3HvBIcrIgGsiM3iyV2ZP9pk2bMHnyZMyZMwcnTpxAhw4d0LdvX2Rns0VYF97feBFhz+fAr1URmrUpwpRFV5D9lxznf3cEAJz+xRlZV+WYsugK/AOK4B9QhGmLL+P8b05IOeyicy5HFw08PMu0m4OTpqpLEj0UHJzUmL7sMhZNa4w7ubaV9jdtcxdDX72Bjyf7mCE6ItMye7L/+OOPMXbsWERERCAwMBCrVq2Ck5MTPv/8c3OHJkkFeeW/9Fzd1QCA0hIZIAPs5f80b+wVAjIb4PQvusl+8zJPPNemLV5/siW+XtEQ6jIQPbSi3v8Lv+xV4uQh10r7FI4avL38Mpa/8whu3bA3Q3RUGypW0DNms1RmHbMvKSlBcnIyZsyYoS2zsbFBaGgokpKSzBiZNGk0wKo5j6BN13z4tS4CALQOKoCDkwZr3vNGxNsZAGRY814jaNQy5GT/8/UZNPoGmre7C1f3Mpw57oy1cY2Qk22PV6MzzPRuiKrXc9AtNG93FxMGtKhy/6vRf+HMcWck/cgxemsi5TF7syb7v//+G2q1Gl5eXjrlXl5eOHfuXKX6xcXFKC7+Z+JYXl5erccoJctmNsblc474aOt5bZl7fTXeXX0JS2c0xvdrGkBmA/QefAvN2xVC9q/v/dBXb2j/3TSwCPb2Aoun+yBixnXIFRz0pIdHQ+8SjI/NwIzhTVFaXPmX96NhuejYLR+vh7U0Q3REtcOiZuPHxcUhJibG3GFYpWUzH8GxRCU+2pKGht6lOvuCet1BfNJZ5N60ha0d4OKmxvAObdCoSXE1ZwNadS6EukyGrKtynZn9RObWvP1d1GtYhuU//qkts7UD2j1agGci/sb29fXRyK8E3507pXPcrE8v4dQxZ7z1XPO6DplMRAMj18a34Al6Zk32DRo0gK2tLbKysnTKs7KyoFKpKtWfMWMGJk+erH2dl5cHHx9OnjGGEMDydx7B0V1uWPBNGlRNSqqt61a/fBw/5bALbv9th0fDqu9ZuXjaETY2Au4NOHBPD5eUQy4Y11u31T5l4VVcTXPA5uUNkZdjhx821NfZ/8lPf2J1tDd+3q2sy1DJxISRM+oFk33NyOVyBAUFYe/evRg8eDAAQKPRYO/evYiKiqpUX6FQQKFQ1HGU1m3ZzMb4aUs9RK+9CEcXjXYc3tlVDYVjeff7j195oEmLIrjVL8PZZGesnP0Inh13Q9tiP3PcCedOOqPDY3fg5KLB2WRnrJrjjSeG3tJO9CN6WNwtsMXlVEedsqJCG9y59U95VZPysv+SI+sqf/9YMj71zowmT56M8PBwdOnSBf/5z3+waNEiFBQUICIiwtyhScL2dQ0AANOG6k5UmrLwCsKezwEAXLugwNq4Rrhz2xZePiUY8UYWhoz7Z4zeXi5w4Ht3fPGRCqUlMqh8SjBk3A2dOkREZD5mT/bPP/88bty4gdmzZyMzMxMdO3bErl27Kk3ao9rxY0bKA+uMfuc6Rr9zvdr9LdrfxeLt56vdT/Swe9A4fF/vDnUUCdUmzsY3s6ioqCq77YmIiExFyt34lvtnChEREenloWjZExER1TZj17fnrXdEREQPOXbjExERkdViy56IiCRByi17JnsiIpIEKSd7duMTERFZObbsiYhIEqTcsmeyJyIiSRAw7vY5S35YN5M9ERFJgpRb9hyzJyIisnJs2RMRkSRIuWXPZE9ERJIg5WTPbnwiIiIrx5Y9ERFJgpRb9kz2REQkCULIIIxI2MYca27sxiciIrJybNkTEZEk8Hn2REREVk7KY/bsxiciIrJybNkTEZEkSHmCHpM9ERFJgpS78ZnsiYhIEqTcsueYPRERkZVjy56IiCRBGNmNb8kteyZ7IiKSBAFACOOOt1TsxiciIrJybNkTEZEkaCCDjCvoERERWS/OxiciIiKrxZY9ERFJgkbIIOOiOkRERNZLCCNn41vwdHx24xMREVk5tuyJiEgSpDxBj8meiIgkgcmeiIjIykl5gh7H7ImIiKwckz0REUlCxWx8YzZDxMXFoWvXrnB1dYWnpycGDx6M1NRUnTpFRUWIjIxE/fr14eLigqFDhyIrK0unzpUrVzBw4EA4OTnB09MT06ZNQ1lZmUGxMNkTEZEklCdsmRGbYdc7cOAAIiMj8fPPPyMxMRGlpaUICwtDQUGBts6kSZOwbds2fP311zhw4AAyMjIwZMgQ7X61Wo2BAweipKQER48exbp16xAfH4/Zs2cbFAvH7ImIiGrBrl27dF7Hx8fD09MTycnJ6NGjB3Jzc7FmzRps3LgRTzzxBABg7dq1CAgIwM8//4xHH30Uu3fvxpkzZ7Bnzx54eXmhY8eOmDt3LqZPn47o6GjI5XK9YmHLnoiIJMG4Vv0/M/nz8vJ0tuLiYr2un5ubCwDw8PAAACQnJ6O0tBShoaHaOq1bt0aTJk2QlJQEAEhKSkK7du3g5eWlrdO3b1/k5eXh9OnTer93JnsiIpIEYYINAHx8fODm5qbd4uLiHnhtjUaDiRMnolu3bmjbti0AIDMzE3K5HO7u7jp1vby8kJmZqa3z70Rfsb9in77YjU9ERGSAq1evQqlUal8rFIoHHhMZGYlTp07h8OHDtRlatZjsiYhIEky1qI5SqdRJ9g8SFRWF7du34+DBg2jcuLG2XKVSoaSkBLdv39Zp3WdlZUGlUmnr/PLLLzrnq5itX1FHH+zGJyIiaTBVP76+lxMCUVFR2LJlC/bt2wd/f3+d/UFBQbC3t8fevXu1Zampqbhy5QpCQkIAACEhIfjjjz+QnZ2trZOYmAilUonAwEC9Y2HLnoiIpMHIlj0MPDYyMhIbN27E999/D1dXV+0Yu5ubGxwdHeHm5obRo0dj8uTJ8PDwgFKpxIQJExASEoJHH30UABAWFobAwEC89NJLmD9/PjIzM/Huu+8iMjJSr+GDCkz2REREtWDlypUAgF69eumUr127FqNGjQIALFy4EDY2Nhg6dCiKi4vRt29frFixQlvX1tYW27dvx/jx4xESEgJnZ2eEh4cjNjbWoFiY7ImISBLq+nn2Qo8DHBwcsHz5cixfvrzaOr6+vtixY4dhF78Hkz0REUmClJ96xwl6REREVo4teyIikgYhM3iSXaXjLRSTPRERSUJdj9k/TNiNT0REZOXYsiciImmowcI4lY63UHol+//+9796n/CZZ56pcTBERES1Rcqz8fVK9oMHD9brZDKZDGq12ph4iIiIyMT0SvYajaa24yAiIqp9FtwVbwyjxuyLiorg4OBgqliIiIhqjZS78Q2eja9WqzF37lw88sgjcHFxwcWLFwEAs2bNwpo1a0weIBERkUnU8VPvHiYGJ/v33nsP8fHxmD9/PuRyuba8bdu2+Oyzz0waHBERERnP4GS/fv16fPLJJxg5ciRsbW215R06dMC5c+dMGhwREZHpyEywWSaDx+z/+usvNG/evFK5RqNBaWmpSYIiIiIyOQnfZ29wyz4wMBCHDh2qVP7NN9+gU6dOJgmKiIiITMfglv3s2bMRHh6Ov/76CxqNBt999x1SU1Oxfv16bN++vTZiJCIiMh5b9vobNGgQtm3bhj179sDZ2RmzZ8/G2bNnsW3bNjz55JO1ESMREZHxKp56Z8xmoWp0n3337t2RmJho6liIiIioFtR4UZ3jx4/j7NmzAMrH8YOCgkwWFBERkalJ+RG3Bif7a9euYcSIEThy5Ajc3d0BALdv38Zjjz2Gr776Co0bNzZ1jERERMbjmL3+xowZg9LSUpw9exY5OTnIycnB2bNnodFoMGbMmNqIkYiIiIxgcMv+wIEDOHr0KFq1aqUta9WqFZYuXYru3bubNDgiIiKTMXaSnZQm6Pn4+FS5eI5arYa3t7dJgiIiIjI1mSjfjDneUhncjb9gwQJMmDABx48f15YdP34cb775Jj788EOTBkdERGQyEn4Qjl4t+3r16kEm+6f7oqCgAMHBwbCzKz+8rKwMdnZ2eOWVVzB48OBaCZSIiIhqRq9kv2jRoloOg4iIqJZxzP7+wsPDazsOIiKi2iXhW+9qvKgOABQVFaGkpESnTKlUGhUQERERmZbBE/QKCgoQFRUFT09PODs7o169ejobERHRQ0nCE/QMTvZvvfUW9u3bh5UrV0KhUOCzzz5DTEwMvL29sX79+tqIkYiIyHgSTvYGd+Nv27YN69evR69evRAREYHu3bujefPm8PX1RUJCAkaOHFkbcRIREVENGdyyz8nJQdOmTQGUj8/n5OQAAB5//HEcPHjQtNERERGZioQfcWtwsm/atCnS09MBAK1bt8bmzZsBlLf4Kx6MQ0RE9LCpWEHPmM1SGZzsIyIi8NtvvwEA3n77bSxfvhwODg6YNGkSpk2bZvIAiYiIyDgGj9lPmjRJ++/Q0FCcO3cOycnJaN68Odq3b2/S4IiIiEyG99nXnK+vL3x9fU0RCxEREdUCvZL9kiVL9D7hG2+8UeNgiIiIaosMRj71zmSR1D29kv3ChQv1OplMJmOyJyIiesjolewrZt8/rJ4L6Qk7G7m5wyCqFbYt3c0dAlGtEepiIK2uLsYH4RAREVk3CU/QM/jWOyIiIrIsbNkTEZE0SLhlz2RPRESSYOwqeJJaQY+IiIgsS42S/aFDh/Diiy8iJCQEf/31FwBgw4YNOHz4sEmDIyIiMhkJP+LW4GT/7bffom/fvnB0dMTJkydRXFwMAMjNzcX7779v8gCJiIhMgslef/PmzcOqVavw6aefwt7eXlverVs3nDhxwqTBERERkfEMnqCXmpqKHj16VCp3c3PD7du3TRETERGRyXGCngFUKhXS0iovd3T48GE0bdrUJEERERGZXMUKesZsFsrgZD927Fi8+eabOHbsGGQyGTIyMpCQkICpU6di/PjxtREjERGR8SQ8Zm9wN/7bb78NjUaDPn36oLCwED169IBCocDUqVMxYcKE2oiRiIiIjGBwspfJZHjnnXcwbdo0pKWlIT8/H4GBgXBxcamN+IiIiExCymP2NV5BTy6XIzAw0JSxEBER1R4ul6u/3r17QyarfpLCvn37jAqIiIiITMvgZN+xY0ed16WlpUhJScGpU6cQHh5uqriIiIhMy8hufEm17BcuXFhleXR0NPLz840OiIiIqFZIuBvfZA/CefHFF/H555+b6nRERERkIiZ7xG1SUhIcHBxMdToiIiLTknDL3uBkP2TIEJ3XQghcv34dx48fx6xZs0wWGBERkSnx1jsDuLm56by2sbFBq1atEBsbi7CwMJMFRkRERKZhULJXq9WIiIhAu3btUK9evdqKiYiIiEzIoAl6tra2CAsL49PtiIjI8kh4bXyDZ+O3bdsWFy9erI1YiIiIak3FmL0xmyEOHjyIp59+Gt7e3pDJZNi6davO/lGjRkEmk+ls/fr106mTk5ODkSNHQqlUwt3dHaNHj67Rbe4GJ/t58+Zh6tSp2L59O65fv468vDydjYiIiICCggJ06NABy5cvr7ZOv379cP36de325Zdf6uwfOXIkTp8+jcTERGzfvh0HDx7EuHHjDI5F7zH72NhYTJkyBQMGDAAAPPPMMzrL5gohIJPJoFarDQ6CiIioTtRhV3z//v3Rv3//+9ZRKBRQqVRV7jt79ix27dqFX3/9FV26dAEALF26FAMGDMCHH34Ib29vvWPRO9nHxMTgtddew08//aT3yYmIiB4aD+F99vv374enpyfq1auHJ554AvPmzUP9+vUBlK9f4+7urk30ABAaGgobGxscO3YMzz77rN7X0TvZC1H+Lnv27Kn3yYmIiKzNvUPWCoUCCoXC4PP069cPQ4YMgb+/Py5cuICZM2eif//+SEpKgq2tLTIzM+Hp6alzjJ2dHTw8PJCZmWnQtQy69e5+T7sjIiJ6mJlqUR0fHx+d8jlz5iA6Otrg8w0fPlz773bt2qF9+/Zo1qwZ9u/fjz59+tQ80CoYlOxbtmz5wISfk5NjVEBERES1wkTd+FevXoVSqdQW16RVX5WmTZuiQYMGSEtLQ58+faBSqZCdna1Tp6ysDDk5OdWO81fHoGQfExNTaQU9IiIiKVEqlTrJ3lSuXbuGmzdvolGjRgCAkJAQ3L59G8nJyQgKCgIA7Nu3DxqNBsHBwQad26BkP3z48ErjB0RERJagrtfGz8/PR1pamvZ1eno6UlJS4OHhAQ8PD8TExGDo0KFQqVS4cOEC3nrrLTRv3hx9+/YFAAQEBKBfv34YO3YsVq1ahdLSUkRFRWH48OEGzcQHDLjPnuP1RERk0ep4Bb3jx4+jU6dO6NSpEwBg8uTJ6NSpE2bPng1bW1v8/vvveOaZZ9CyZUuMHj0aQUFBOHTokM6wQEJCAlq3bo0+ffpgwIABePzxx/HJJ58Y/NYNno1PRERED9arV6/75s4ff/zxgefw8PDAxo0bjY5F72Sv0WiMvhgREZHZPIT32dcVgx9xS0REZIn4PHsiIiJrJ+GWvcEPwiEiIiLLwpY9ERFJg4Rb9kz2REQkCVIes2c3PhERkZVjy56IiKSB3fhERETWjd34REREZLXYsiciImlgNz4REZGVk3CyZzc+ERGRlWPLnoiIJEH2v82Y4y0Vkz0REUmDhLvxmeyJiEgSeOsdERERWS227ImISBrYjU9ERCQBFpywjcFufCIiIivHlj0REUmClCfoMdkTEZE0SHjMnt34REREVo4teyIikgR24xMREVk7duMTERGRtWLLnoiIJIHd+ERERNZOwt34TPZERCQNEk72HLMnIiKycmzZExGRJHDMnoiIyNqxG5+IiIisFVv2REQkCTIhIBM1b54bc6y5MdkTEZE0sBufiIiIrBVb9kREJAmcjU9ERGTt2I1PRERE1ooteyIikgR24xMREVk7CXfjM9kTEZEkSLllzzF7IiIiK8eWPRERSQO78YmIiKyfJXfFG4Pd+ERERFaOLXsiIpIGIco3Y463UEz2REQkCZyNT0RERFaLLXsiIpIGzsYnIiKybjJN+WbM8ZaK3fhERERWji17qmTk+IsYOf6STtnVdCe8OuhRAEC9+sUYPTkNHUNuwcm5DNcuOWHTp344ssfTDNESGW7tV7vgpSqsVL59S1Os/zwQL0acQecu2WjoVYjc2wokHfbGhs8DUVhgb4ZoyWTYjW8eBw8exIIFC5CcnIzr169jy5YtGDx4sDlDov+5lOaMd8Z21L5Wq2Xaf0957wycXcsQ+0Z75N2yR68BmXh7wSm8OaIrLp5zNUO0RIZ589XesLX95ze3r38e3v/oMA4deAT1G9xF/fpF+GxlO1y57Aovr0JETU5B/QZ38f6cR80YNRmLs/HNpKCgAB06dMDy5cvNGQZVQV0mw62bCu2Wd1uu3RfQMQ/bvmyMP08pkfmXI7761B8Fd+zQIvCOGSMm0l9ergK3chy0239CriPjL2f8kdIAl9Pd8N6cR/FLUiNkZrjgt5OeWPdZIIJDMmFja8GDtvTPffbGbBbKrC37/v37o3///uYMgarxiG8hNuw5jJISG5z7zQ3xi5vhRqYDAOBsihI9+mbjl4MNUHDHDt37ZkOu0OD3X93NGzRRDdjZadD7yavYsrk5AFmVdZxdSlFYaAeNmtOcyDJZ1Jh9cXExiouLta/z8vLMGI31Sv3DDR+/G4hrl5zg0bAYL7yWjgXxyRg/JBh3C+0QN60t3p5/GpsPH0JZqQzFRTaYO7Edrl91MnfoRAYLeTwDLi6l2LPLt8r9SrdijHjpHHZu86/jyMjU2I1vIeLi4uDm5qbdfHx8zB2SVTp+uD4OJ3ri0nkXnDhaH3MiO8DZtQzd+2YDAF6KTIeLsgwzxnbEmyO6YMuGJpix4DT8WuSbOXIiw4UNuITjx7yQc9Ox0j5Hp1LExB3FlctKJMQHmCE6Milhgs1CWVSynzFjBnJzc7Xb1atXzR2SJBTcscdfl53g7XMXqsaFeOaFa1g4uzV+O+aB9D9dsXGVP86fccVTz18zd6hEBvH0KkTHoGz8+INfpX2OjqWYO/8ICu/aYe6sR6FmFz5ZMIvqxlcoFFAoFOYOQ3IcHMvQyOcu9m2Xw8GxfIKS0OiObWrUMsj4u5AszJP9LyH3tgK//KzSKXd0KsW8BUdQWmqD2JkhKC2xNVOEZErsxif6l9FTzqNt0C14et9FQIdczFr0BzRqGfbv9MLVdCf8ddkRE2afQ8u2eVA1LsSzL19Bp5AcJO1rYO7QifQmkwk82e8y9vzoqzPxztGpFO99eBgODmVYNL8znJzLUM+jCPU8imBjY8G/7Ymz8c0lPz8faWlp2tfp6elISUmBh4cHmjRpYsbIpK2BZzGmf3AaSvdS5N6S4/QJN0x6MQh5t8pvv5sT2QEREy9gztLf4OikRsYVJ3z8bgCOH2ayJ8vRMSgbnqq7SNyhOzGvecvbaB14CwDw+cbdOvtGDe+L7EznOouRyFRkQpjvT5X9+/ejd+/elcrDw8MRHx//wOPz8vLg5uaGPvUjYGcjf2B9Iovk4W7uCIhqTZm6GHvTFiE3NxdKpbJWrlGRK0L6x8LO3qHG5ykrLULSztm1GmttMWs3fq9evSCEqLTpk+iJiIgMUsez8Q8ePIinn34a3t7ekMlk2Lp1q244QmD27Nlo1KgRHB0dERoaivPnz+vUycnJwciRI6FUKuHu7o7Ro0cjP9/wO584Zk9ERFQLHrRK7Pz587FkyRKsWrUKx44dg7OzM/r27YuioiJtnZEjR+L06dNITEzE9u3bcfDgQYwbN87gWCxqNj4REVFN1fVs/PutEiuEwKJFi/Duu+9i0KBBAID169fDy8sLW7duxfDhw3H27Fns2rULv/76K7p06QIAWLp0KQYMGIAPP/wQ3t7eesfClj0REUmDRhi/oXwOwL+3f6/sqq/09HRkZmYiNDRUW+bm5obg4GAkJSUBAJKSkuDu7q5N9AAQGhoKGxsbHDt2zKDrMdkTEZE0mGjM3sfHR2c117i4OINDyczMBAB4eXnplHt5eWn3ZWZmwtNT99HhdnZ28PDw0NbRF7vxiYiIDHD16lWd2fiWsNgbW/ZERCQJMvwzbl+j7X/nUSqVOltNkr1KVb5qY1ZWlk55VlaWdp9KpUJ2drbO/rKyMuTk5Gjr6IvJnoiIpOEhWkHP398fKpUKe/fu1Zbl5eXh2LFjCAkJAQCEhITg9u3bSE5O1tbZt28fNBoNgoODDboeu/GJiIhqwYNWiZ04cSLmzZuHFi1awN/fH7NmzYK3tzcGDx4MAAgICEC/fv0wduxYrFq1CqWlpYiKisLw4cMNmokPMNkTEZFE1PWtd8ePH9dZJXby5MkA/lkl9q233kJBQQHGjRuH27dv4/HHH8euXbvg4PDPKn8JCQmIiopCnz59YGNjg6FDh2LJkiUGx85kT0RE0mDsM+kNPLZildjqyGQyxMbGIjY2tto6Hh4e2Lhxo2EXrgLH7ImIiKwcW/ZERCQJMiEgM2KSnTHHmhuTPRERSYPmf5sxx1soduMTERFZObbsiYhIEtiNT0REZO3qeDb+w4TJnoiIpMHYVfAsuGXPMXsiIiIrx5Y9ERFJQl2voPcwYbInIiJpYDc+ERERWSu27ImISBJkmvLNmOMtFZM9ERFJA7vxiYiIyFqxZU9ERNLARXWIiIism5SXy2U3PhERkZVjy56IiKRBwhP0mOyJiEgaBIx7Jr3l5nomeyIikgaO2RMREZHVYsueiIikQcDIMXuTRVLnmOyJiEgaJDxBj934REREVo4teyIikgYNAJmRx1soJnsiIpIEzsYnIiIiq8WWPRERSYOEJ+gx2RMRkTRIONmzG5+IiMjKsWVPRETSIOGWPZM9ERFJA2+9IyIism689Y6IiIisFlv2REQkDRyzJyIisnIaAciMSNgay0327MYnIiKycmzZExGRNLAbn4iIyNoZmexhucme3fhERERWji17IiKSBnbjExERWTmNgFFd8ZyNT0RERA8rtuyJiEgahKZ8M+Z4C8VkT0RE0sAxeyIiIivHMXsiIiKyVmzZExGRNLAbn4iIyMoJGJnsTRZJnWM3PhERkZVjy56IiKSB3fhERERWTqMBYMS98hrLvc+e3fhERERWji17IiKSBnbjExERWTkJJ3t24xMREVk5tuyJiEgaJLxcLpM9ERFJghAaCCOeXGfMsebGZE9ERNIghHGtc47ZExER0cOKLXsiIpIGYeSYvQW37JnsiYhIGjQaQGbEuLsFj9mzG5+IiMjKMdkTEZE0VCyqY8xmgOjoaMhkMp2tdevW2v1FRUWIjIxE/fr14eLigqFDhyIrK8vU7xoAkz0REUmE0GiM3gzVpk0bXL9+XbsdPnxYu2/SpEnYtm0bvv76axw4cAAZGRkYMmSIKd+yFsfsiYiIaomdnR1UKlWl8tzcXKxZswYbN27EE088AQBYu3YtAgIC8PPPP+PRRx81aRxs2RMRkTSYqBs/Ly9PZysuLq72kufPn4e3tzeaNm2KkSNH4sqVKwCA5ORklJaWIjQ0VFu3devWaNKkCZKSkkz+1pnsiYhIGjTC+A2Aj48P3NzctFtcXFyVlwsODkZ8fDx27dqFlStXIj09Hd27d8edO3eQmZkJuVwOd3d3nWO8vLyQmZlp8rfObnwiIiIDXL16FUqlUvtaoVBUWa9///7af7dv3x7BwcHw9fXF5s2b4ejoWOtx/htb9kREJA1ClN8rX+OtvGWvVCp1tuqS/b3c3d3RsmVLpKWlQaVSoaSkBLdv39apk5WVVeUYv7GY7ImISBKERhi9GSM/Px8XLlxAo0aNEBQUBHt7e+zdu1e7PzU1FVeuXEFISIixb7USduMTEZE0CA2AultBb+rUqXj66afh6+uLjIwMzJkzB7a2thgxYgTc3NwwevRoTJ48GR4eHlAqlZgwYQJCQkJMPhMfYLInIiKqFdeuXcOIESNw8+ZNNGzYEI8//jh+/vlnNGzYEACwcOFC2NjYYOjQoSguLkbfvn2xYsWKWomFyZ6IiCRBaASErOZd8cLAFfS++uqr++53cHDA8uXLsXz58hrHpC8meyIikoY67sZ/mFh0sq/4K6tMU2LmSIhqkbr6BTuILF2Zpvz7bWiruUbXQqlRT7gtQ6npgqljFp3s79y5AwA4cCvBzJEQ1aKb5g6AqPbduXMHbm5utXJuuVwOlUqFw5k7jD6XSqWCXC43QVR1Sybq4s+pWqLRaJCRkQFXV1fIZDJzhyMJeXl58PHxqbSoBJE14Pe77gkhcOfOHXh7e8PGpvbuBi8qKkJJifG9wHK5HA4ODiaIqG5ZdMvexsYGjRs3NncYklSxmASRNeL3u27VVov+3xwcHCwySZsKF9UhIiKyckz2REREVo7JngyiUCgwZ84cvdeCJrIk/H6TtbLoCXpERET0YGzZExERWTkmeyIiIivHZE9ERGTlmOyJiIisHJM96W358uXw8/ODg4MDgoOD8csvv5g7JCKTOHjwIJ5++ml4e3tDJpNh69at5g6JyKSY7EkvmzZtwuTJkzFnzhycOHECHTp0QN++fZGdnW3u0IiMVlBQgA4dOtTJo0aJzIG33pFegoOD0bVrVyxbtgxA+XMJfHx8MGHCBLz99ttmjo7IdGQyGbZs2YLBgwebOxQik2HLnh6opKQEycnJCA0N1ZbZ2NggNDQUSUlJZoyMiIj0wWRPD/T3339DrVbDy8tLp9zLywuZmZlmioqIiPTFZE9ERGTlmOzpgRo0aABbW1tkZWXplGdlZUGlUpkpKiIi0heTPT2QXC5HUFAQ9u7dqy3TaDTYu3cvQkJCzBgZERHpw87cAZBlmDx5MsLDw9GlSxf85z//waJFi1BQUICIiAhzh0ZktPz8fKSlpWlfp6enIyUlBR4eHmjSpIkZIyMyDd56R3pbtmwZFixYgMzMTHTs2BFLlixBcHCwucMiMtr+/fvRu3fvSuXh4eGIj4+v+4CITIzJnoiIyMpxzJ6IiMjKMdkTERFZOSZ7IiIiK8dkT0REZOWY7ImIiKwckz0REZGVY7InIiKyckz2REYaNWqUzrPPe/XqhYkTJ9Z5HPv374dMJsPt27errSOTybB161a9zxkdHY2OHTsaFdelS5cgk8mQkpJi1HmIqOaY7MkqjRo1CjKZDDKZDHK5HM2bN0dsbCzKyspq/drfffcd5s6dq1ddfRI0EZGxuDY+Wa1+/fph7dq1KC4uxo4dOxAZGQl7e3vMmDGjUt2SkhLI5XKTXNfDw8Mk5yEiMhW27MlqKRQKqFQq+Pr6Yvz48QgNDcV///tfAP90vb/33nvw9vZGq1atAABXr17FsGHD4O7uDg8PDwwaNAiXLl3SnlOtVmPy5Mlwd3dH/fr18dZbb+HeFafv7cYvLi7G9OnT4ePjA4VCgebNm2PNmjW4dOmSdj32evXqQSaTYdSoUQDKnyoYFxcHf39/ODo6okOHDvjmm290rrNjxw60bNkSjo6O6N27t06c+po+fTpatmwJJycnNG3aFLNmzUJpaWmleqtXr4aPjw+cnJwwbNgw5Obm6uz/7LPPEBAQAAcHB7Ru3RorVqwwOBYiqj1M9iQZjo6OKCkp0b7eu3cvUlNTkZiYiO3bt6O0tBR9+/aFq6srDh06hCNHjsDFxQX9+vXTHvfRRx8hPj4en3/+OQ4fPoycnBxs2bLlvtd9+eWX8eWXX2LJkiU4e/YsVq9eDRcXF/j4+ODbb78FAKSmpuL69etYvHgxACAuLg7r16/HqlWrcPr0aUyaNAkvvvgiDhw4AKD8j5IhQ4bg6aefRkpKCsaMGYO3337b4M/E1dUV8fHxOHPmDBYvXoxPP/0UCxcu1KmTlpaGzZs3Y9u2bdi1axdOnjyJ119/Xbs/ISEBs2fPxnvvvYezZ8/i/fffx6xZs7Bu3TqD4yGiWiKIrFB4eLgYNGiQEEIIjUYjEhMThUKhEFOnTtXu9/LyEsXFxdpjNmzYIFq1aiU0Go22rLi4WDg6Oooff/xRCCFEo0aNxPz587X7S0tLRePGjbXXEkKInj17ijfffFMIIURqaqoAIBITE6uM86effhIAxK1bt7RlRUVFwsnJSRw9elSn7ujRo8WIESOEEELMmDFDBAYG6uyfPn16pXPdC4DYsmVLtfsXLFgggoKCtK/nzJkjbG1txbVr17RlO3fuFDY2NuL69etCCCGaNWsmNm7cqHOeuXPnipCQECGEEOnp6QKAOHnyZLXXJaLaxTF7slrbt2+Hi4sLSktLodFo8MILLyA6Olq7v127djrj9L/99hvS0tLg6uqqc56ioiJcuHABubm5uH79us5jfe3s7NClS5dKXfkVUlJSYGtri549e+odd1paGgoLC/Hkk0/qlJeUlKBTp04AgLNnz1Z6vHBISIje16iwadMmLFmyBBcuXEB+fj7KysqgVCp16jRp0gSPPPKIznU0Gg1SU1Ph6uqKCxcuYPTo0Rg7dqy2TllZGdzc3AyOh4hqB5M9Wa3evXtj5cqVkMvl8Pb2hp2d7tfd2dlZ53V+fj6CgoKQkJBQ6VwNGzasUQyOjo4GH5Ofnw8A+OGHH3SSLFA+D8FUkpKSMHLkSMTExKBv375wc3PDV199hY8++sjgWD/99NNKf3zY2tqaLFYiMg6TPVktZ2dnNG/eXO/6nTt3xqZNm+Dp6VmpdVuhUaNGOHbsGHr06AGgvAWbnJyMzp07V1m/Xbt20Gg0OHDgAEJDQyvtr+hZUKvV2rLAwEAoFApcuXKl2h6BgIAA7WTDCj///POD3+S/HD16FL6+vnjnnXe0ZZcvX65U78qVK8jIyIC3t7f2OjY2NmjVqhW8vLzg7e2NixcvYuTIkQZdn4jqDifoEf3PyJEj0aBBAwwaNAiHDh1Ceno69u/fjzfeeAPXrl0DALz55pv4f//v/2Hr1q04d+4cXn/99fveI+/n54fw8HC88sor2Lp1q/acmzdvBgD4+vpCJpNh+/btuHHjBvLz8+Hq6oqpU6di0qRJWLduHS5cuIATJ05g6dKl2klvr732Gs6fP49p06YhNTUVGzduRHx8vEHvt0WLFrhy5Qq++uorXLhwAUuWLKlysqGDgwPCw8Px22+/4dChQ3jjjTcwbNgwqFQqAEBMTAzi4uKwZMkS/Pnnn/jjjz+wdu1afPzxxwbFQ0S1h8me6H+cnJxw8OBBNGnSBEOGDEFAQABGjx6NoqIibUt/ypQpeOmllxAeHo6QkBC4urri2Wefve95V65cieeeew6vv/46WrdujbFjx6KgoAAA8MgjjyAmJgZvv/02vLy8EBUVBQCYO3cuZs2ahbi4OAQEBKBfv3744Ycf4O/vD6B8HP3bb7/F1q1b0aFDB6xatQrvv/++Qe/3mWeewaRJkxAVFYWOHTvi6NGjmDVrVqV6zZs3x5AhQzBgwACEhYWhffv2OrfWjRkzBp999hnWrl2Ldu3aoWfPnoiPj9fGSkTmJxPVzSwiIiIiq8CWPRERkZVjsiciIrJyTPZERERWjsmeiIjIyjHZExERWTkmeyIiIivHZE9ERGTlmOyJiIisHJM9ERGRlWOyJyIisnJM9kRERFaOyZ6IiMjK/X+eHRJBJCEmSwAAAABJRU5ErkJggg=="},"metadata":{}},{"name":"stdout","text":"Learning rate set to 0.013477\n0:\tlearn: 0.6838656\ttotal: 1.63ms\tremaining: 1.63s\n1:\tlearn: 0.6758078\ttotal: 2.98ms\tremaining: 1.49s\n2:\tlearn: 0.6674481\ttotal: 4.32ms\tremaining: 1.43s\n3:\tlearn: 0.6583720\ttotal: 5.57ms\tremaining: 1.39s\n4:\tlearn: 0.6509284\ttotal: 6.87ms\tremaining: 1.37s\n5:\tlearn: 0.6431915\ttotal: 8.11ms\tremaining: 1.34s\n6:\tlearn: 0.6373617\ttotal: 9.34ms\tremaining: 1.32s\n7:\tlearn: 0.6305452\ttotal: 10.6ms\tremaining: 1.31s\n8:\tlearn: 0.6240415\ttotal: 11.9ms\tremaining: 1.3s\n9:\tlearn: 0.6181451\ttotal: 13.1ms\tremaining: 1.3s\n10:\tlearn: 0.6116032\ttotal: 14.7ms\tremaining: 1.32s\n11:\tlearn: 0.6057016\ttotal: 16.1ms\tremaining: 1.32s\n12:\tlearn: 0.5992679\ttotal: 17.4ms\tremaining: 1.32s\n13:\tlearn: 0.5938989\ttotal: 18.7ms\tremaining: 1.31s\n14:\tlearn: 0.5881622\ttotal: 20ms\tremaining: 1.31s\n15:\tlearn: 0.5824536\ttotal: 21.3ms\tremaining: 1.31s\n16:\tlearn: 0.5772842\ttotal: 22.6ms\tremaining: 1.31s\n17:\tlearn: 0.5721793\ttotal: 23.9ms\tremaining: 1.3s\n18:\tlearn: 0.5690468\ttotal: 25.2ms\tremaining: 1.3s\n19:\tlearn: 0.5644471\ttotal: 26.6ms\tremaining: 1.3s\n20:\tlearn: 0.5608056\ttotal: 27.9ms\tremaining: 1.3s\n21:\tlearn: 0.5562242\ttotal: 29.4ms\tremaining: 1.31s\n22:\tlearn: 0.5522125\ttotal: 30.8ms\tremaining: 1.31s\n23:\tlearn: 0.5479600\ttotal: 32.2ms\tremaining: 1.31s\n24:\tlearn: 0.5443633\ttotal: 33.6ms\tremaining: 1.31s\n25:\tlearn: 0.5405790\ttotal: 34.9ms\tremaining: 1.3s\n26:\tlearn: 0.5364419\ttotal: 36.2ms\tremaining: 1.3s\n27:\tlearn: 0.5329990\ttotal: 37.5ms\tremaining: 1.3s\n28:\tlearn: 0.5298083\ttotal: 39.1ms\tremaining: 1.31s\n29:\tlearn: 0.5257863\ttotal: 40.4ms\tremaining: 1.31s\n30:\tlearn: 0.5225180\ttotal: 41.8ms\tremaining: 1.3s\n31:\tlearn: 0.5197893\ttotal: 43ms\tremaining: 1.3s\n32:\tlearn: 0.5166048\ttotal: 44.3ms\tremaining: 1.3s\n33:\tlearn: 0.5133304\ttotal: 45.7ms\tremaining: 1.3s\n34:\tlearn: 0.5101360\ttotal: 47ms\tremaining: 1.29s\n35:\tlearn: 0.5067611\ttotal: 48.5ms\tremaining: 1.3s\n36:\tlearn: 0.5038938\ttotal: 50ms\tremaining: 1.3s\n37:\tlearn: 0.5012076\ttotal: 51.3ms\tremaining: 1.3s\n38:\tlearn: 0.4986865\ttotal: 52.6ms\tremaining: 1.3s\n39:\tlearn: 0.4960242\ttotal: 53.9ms\tremaining: 1.29s\n40:\tlearn: 0.4941094\ttotal: 55.2ms\tremaining: 1.29s\n41:\tlearn: 0.4917178\ttotal: 56.5ms\tremaining: 1.29s\n42:\tlearn: 0.4894410\ttotal: 57.8ms\tremaining: 1.28s\n43:\tlearn: 0.4876576\ttotal: 59ms\tremaining: 1.28s\n44:\tlearn: 0.4861331\ttotal: 60.3ms\tremaining: 1.28s\n45:\tlearn: 0.4833094\ttotal: 61.5ms\tremaining: 1.28s\n46:\tlearn: 0.4809459\ttotal: 62.9ms\tremaining: 1.27s\n47:\tlearn: 0.4789782\ttotal: 64.1ms\tremaining: 1.27s\n48:\tlearn: 0.4774782\ttotal: 65.3ms\tremaining: 1.27s\n49:\tlearn: 0.4753783\ttotal: 66.6ms\tremaining: 1.26s\n50:\tlearn: 0.4728362\ttotal: 67.9ms\tremaining: 1.26s\n51:\tlearn: 0.4706000\ttotal: 69.1ms\tremaining: 1.26s\n52:\tlearn: 0.4685507\ttotal: 70.4ms\tremaining: 1.26s\n53:\tlearn: 0.4666814\ttotal: 71.7ms\tremaining: 1.26s\n54:\tlearn: 0.4648348\ttotal: 73ms\tremaining: 1.25s\n55:\tlearn: 0.4628744\ttotal: 74.2ms\tremaining: 1.25s\n56:\tlearn: 0.4612058\ttotal: 75.5ms\tremaining: 1.25s\n57:\tlearn: 0.4591243\ttotal: 76.9ms\tremaining: 1.25s\n58:\tlearn: 0.4571499\ttotal: 78.2ms\tremaining: 1.25s\n59:\tlearn: 0.4556636\ttotal: 79.5ms\tremaining: 1.25s\n60:\tlearn: 0.4540737\ttotal: 80.8ms\tremaining: 1.24s\n61:\tlearn: 0.4524821\ttotal: 82ms\tremaining: 1.24s\n62:\tlearn: 0.4511638\ttotal: 83.3ms\tremaining: 1.24s\n63:\tlearn: 0.4496792\ttotal: 84.5ms\tremaining: 1.24s\n64:\tlearn: 0.4482901\ttotal: 85.9ms\tremaining: 1.24s\n65:\tlearn: 0.4468370\ttotal: 87.1ms\tremaining: 1.23s\n66:\tlearn: 0.4452703\ttotal: 88.4ms\tremaining: 1.23s\n67:\tlearn: 0.4441687\ttotal: 89.7ms\tremaining: 1.23s\n68:\tlearn: 0.4427134\ttotal: 91ms\tremaining: 1.23s\n69:\tlearn: 0.4411629\ttotal: 92.4ms\tremaining: 1.23s\n70:\tlearn: 0.4398318\ttotal: 93.8ms\tremaining: 1.23s\n71:\tlearn: 0.4385469\ttotal: 95.2ms\tremaining: 1.23s\n72:\tlearn: 0.4373829\ttotal: 96.5ms\tremaining: 1.23s\n73:\tlearn: 0.4360992\ttotal: 97.8ms\tremaining: 1.22s\n74:\tlearn: 0.4350130\ttotal: 99.1ms\tremaining: 1.22s\n75:\tlearn: 0.4340907\ttotal: 100ms\tremaining: 1.22s\n76:\tlearn: 0.4330526\ttotal: 102ms\tremaining: 1.22s\n77:\tlearn: 0.4321139\ttotal: 103ms\tremaining: 1.22s\n78:\tlearn: 0.4307044\ttotal: 104ms\tremaining: 1.22s\n79:\tlearn: 0.4299842\ttotal: 105ms\tremaining: 1.21s\n80:\tlearn: 0.4291736\ttotal: 107ms\tremaining: 1.21s\n81:\tlearn: 0.4280273\ttotal: 108ms\tremaining: 1.21s\n82:\tlearn: 0.4269721\ttotal: 109ms\tremaining: 1.21s\n83:\tlearn: 0.4259817\ttotal: 111ms\tremaining: 1.21s\n84:\tlearn: 0.4250015\ttotal: 112ms\tremaining: 1.21s\n85:\tlearn: 0.4239173\ttotal: 114ms\tremaining: 1.21s\n86:\tlearn: 0.4229586\ttotal: 115ms\tremaining: 1.21s\n87:\tlearn: 0.4220666\ttotal: 116ms\tremaining: 1.2s\n88:\tlearn: 0.4210140\ttotal: 117ms\tremaining: 1.2s\n89:\tlearn: 0.4200321\ttotal: 119ms\tremaining: 1.2s\n90:\tlearn: 0.4190811\ttotal: 120ms\tremaining: 1.2s\n91:\tlearn: 0.4178803\ttotal: 121ms\tremaining: 1.2s\n92:\tlearn: 0.4171507\ttotal: 123ms\tremaining: 1.2s\n93:\tlearn: 0.4162712\ttotal: 124ms\tremaining: 1.19s\n94:\tlearn: 0.4150368\ttotal: 125ms\tremaining: 1.19s\n95:\tlearn: 0.4140393\ttotal: 126ms\tremaining: 1.19s\n96:\tlearn: 0.4131950\ttotal: 128ms\tremaining: 1.19s\n97:\tlearn: 0.4120038\ttotal: 129ms\tremaining: 1.19s\n98:\tlearn: 0.4112120\ttotal: 130ms\tremaining: 1.19s\n99:\tlearn: 0.4107803\ttotal: 131ms\tremaining: 1.18s\n100:\tlearn: 0.4099592\ttotal: 133ms\tremaining: 1.18s\n101:\tlearn: 0.4094548\ttotal: 134ms\tremaining: 1.18s\n102:\tlearn: 0.4086998\ttotal: 135ms\tremaining: 1.18s\n103:\tlearn: 0.4080693\ttotal: 137ms\tremaining: 1.18s\n104:\tlearn: 0.4072141\ttotal: 138ms\tremaining: 1.17s\n105:\tlearn: 0.4068332\ttotal: 139ms\tremaining: 1.17s\n106:\tlearn: 0.4061805\ttotal: 141ms\tremaining: 1.17s\n107:\tlearn: 0.4057864\ttotal: 142ms\tremaining: 1.17s\n108:\tlearn: 0.4050086\ttotal: 143ms\tremaining: 1.17s\n109:\tlearn: 0.4043780\ttotal: 144ms\tremaining: 1.17s\n110:\tlearn: 0.4035184\ttotal: 146ms\tremaining: 1.17s\n111:\tlearn: 0.4029431\ttotal: 147ms\tremaining: 1.17s\n112:\tlearn: 0.4023117\ttotal: 148ms\tremaining: 1.16s\n113:\tlearn: 0.4017164\ttotal: 150ms\tremaining: 1.16s\n114:\tlearn: 0.4010964\ttotal: 151ms\tremaining: 1.16s\n115:\tlearn: 0.4002701\ttotal: 152ms\tremaining: 1.16s\n116:\tlearn: 0.3995851\ttotal: 153ms\tremaining: 1.16s\n117:\tlearn: 0.3988357\ttotal: 155ms\tremaining: 1.16s\n118:\tlearn: 0.3981552\ttotal: 156ms\tremaining: 1.16s\n119:\tlearn: 0.3975807\ttotal: 158ms\tremaining: 1.16s\n120:\tlearn: 0.3969913\ttotal: 159ms\tremaining: 1.16s\n121:\tlearn: 0.3963573\ttotal: 160ms\tremaining: 1.15s\n122:\tlearn: 0.3957974\ttotal: 162ms\tremaining: 1.15s\n123:\tlearn: 0.3952270\ttotal: 163ms\tremaining: 1.15s\n124:\tlearn: 0.3946346\ttotal: 164ms\tremaining: 1.15s\n125:\tlearn: 0.3941434\ttotal: 166ms\tremaining: 1.15s\n126:\tlearn: 0.3935366\ttotal: 167ms\tremaining: 1.15s\n127:\tlearn: 0.3928694\ttotal: 168ms\tremaining: 1.15s\n128:\tlearn: 0.3923522\ttotal: 170ms\tremaining: 1.15s\n129:\tlearn: 0.3917551\ttotal: 171ms\tremaining: 1.15s\n130:\tlearn: 0.3912321\ttotal: 173ms\tremaining: 1.14s\n131:\tlearn: 0.3907711\ttotal: 174ms\tremaining: 1.14s\n132:\tlearn: 0.3903551\ttotal: 175ms\tremaining: 1.14s\n133:\tlearn: 0.3895483\ttotal: 176ms\tremaining: 1.14s\n134:\tlearn: 0.3891096\ttotal: 178ms\tremaining: 1.14s\n135:\tlearn: 0.3886794\ttotal: 179ms\tremaining: 1.14s\n136:\tlearn: 0.3881677\ttotal: 181ms\tremaining: 1.14s\n137:\tlearn: 0.3875279\ttotal: 182ms\tremaining: 1.14s\n138:\tlearn: 0.3870149\ttotal: 183ms\tremaining: 1.14s\n139:\tlearn: 0.3864852\ttotal: 186ms\tremaining: 1.14s\n140:\tlearn: 0.3860731\ttotal: 187ms\tremaining: 1.14s\n141:\tlearn: 0.3855636\ttotal: 189ms\tremaining: 1.14s\n142:\tlearn: 0.3851173\ttotal: 190ms\tremaining: 1.14s\n143:\tlearn: 0.3847052\ttotal: 191ms\tremaining: 1.14s\n144:\tlearn: 0.3839497\ttotal: 193ms\tremaining: 1.14s\n145:\tlearn: 0.3834139\ttotal: 194ms\tremaining: 1.14s\n146:\tlearn: 0.3829551\ttotal: 196ms\tremaining: 1.14s\n147:\tlearn: 0.3825137\ttotal: 197ms\tremaining: 1.13s\n148:\tlearn: 0.3820628\ttotal: 198ms\tremaining: 1.13s\n149:\tlearn: 0.3816702\ttotal: 200ms\tremaining: 1.13s\n150:\tlearn: 0.3812220\ttotal: 201ms\tremaining: 1.13s\n151:\tlearn: 0.3807033\ttotal: 202ms\tremaining: 1.13s\n152:\tlearn: 0.3802626\ttotal: 204ms\tremaining: 1.13s\n153:\tlearn: 0.3798004\ttotal: 205ms\tremaining: 1.13s\n154:\tlearn: 0.3796631\ttotal: 206ms\tremaining: 1.12s\n155:\tlearn: 0.3794263\ttotal: 207ms\tremaining: 1.12s\n156:\tlearn: 0.3790312\ttotal: 208ms\tremaining: 1.12s\n157:\tlearn: 0.3785859\ttotal: 210ms\tremaining: 1.12s\n158:\tlearn: 0.3782018\ttotal: 211ms\tremaining: 1.12s\n159:\tlearn: 0.3776881\ttotal: 212ms\tremaining: 1.11s\n160:\tlearn: 0.3772753\ttotal: 214ms\tremaining: 1.11s\n161:\tlearn: 0.3767445\ttotal: 215ms\tremaining: 1.11s\n162:\tlearn: 0.3762077\ttotal: 216ms\tremaining: 1.11s\n163:\tlearn: 0.3757532\ttotal: 218ms\tremaining: 1.11s\n164:\tlearn: 0.3754873\ttotal: 219ms\tremaining: 1.11s\n165:\tlearn: 0.3750546\ttotal: 220ms\tremaining: 1.11s\n166:\tlearn: 0.3746284\ttotal: 222ms\tremaining: 1.1s\n167:\tlearn: 0.3742116\ttotal: 223ms\tremaining: 1.1s\n168:\tlearn: 0.3738200\ttotal: 224ms\tremaining: 1.1s\n169:\tlearn: 0.3734268\ttotal: 226ms\tremaining: 1.1s\n170:\tlearn: 0.3731184\ttotal: 227ms\tremaining: 1.1s\n171:\tlearn: 0.3727546\ttotal: 228ms\tremaining: 1.1s\n172:\tlearn: 0.3723824\ttotal: 230ms\tremaining: 1.1s\n173:\tlearn: 0.3720684\ttotal: 231ms\tremaining: 1.1s\n174:\tlearn: 0.3716427\ttotal: 232ms\tremaining: 1.09s\n175:\tlearn: 0.3711650\ttotal: 234ms\tremaining: 1.09s\n176:\tlearn: 0.3707969\ttotal: 235ms\tremaining: 1.09s\n177:\tlearn: 0.3704168\ttotal: 236ms\tremaining: 1.09s\n178:\tlearn: 0.3699671\ttotal: 238ms\tremaining: 1.09s\n179:\tlearn: 0.3695791\ttotal: 239ms\tremaining: 1.09s\n180:\tlearn: 0.3691587\ttotal: 240ms\tremaining: 1.09s\n181:\tlearn: 0.3688321\ttotal: 241ms\tremaining: 1.08s\n182:\tlearn: 0.3684468\ttotal: 243ms\tremaining: 1.08s\n183:\tlearn: 0.3681522\ttotal: 244ms\tremaining: 1.08s\n184:\tlearn: 0.3679301\ttotal: 245ms\tremaining: 1.08s\n185:\tlearn: 0.3676040\ttotal: 247ms\tremaining: 1.08s\n186:\tlearn: 0.3672947\ttotal: 248ms\tremaining: 1.08s\n187:\tlearn: 0.3668426\ttotal: 249ms\tremaining: 1.08s\n188:\tlearn: 0.3664749\ttotal: 251ms\tremaining: 1.08s\n189:\tlearn: 0.3659812\ttotal: 252ms\tremaining: 1.07s\n190:\tlearn: 0.3656888\ttotal: 253ms\tremaining: 1.07s\n191:\tlearn: 0.3653473\ttotal: 255ms\tremaining: 1.07s\n192:\tlearn: 0.3649575\ttotal: 256ms\tremaining: 1.07s\n193:\tlearn: 0.3645062\ttotal: 257ms\tremaining: 1.07s\n194:\tlearn: 0.3641390\ttotal: 259ms\tremaining: 1.07s\n195:\tlearn: 0.3638571\ttotal: 260ms\tremaining: 1.06s\n196:\tlearn: 0.3635655\ttotal: 261ms\tremaining: 1.06s\n197:\tlearn: 0.3631415\ttotal: 262ms\tremaining: 1.06s\n198:\tlearn: 0.3628179\ttotal: 264ms\tremaining: 1.06s\n199:\tlearn: 0.3625360\ttotal: 265ms\tremaining: 1.06s\n200:\tlearn: 0.3623035\ttotal: 266ms\tremaining: 1.06s\n201:\tlearn: 0.3619772\ttotal: 267ms\tremaining: 1.06s\n202:\tlearn: 0.3616644\ttotal: 269ms\tremaining: 1.05s\n203:\tlearn: 0.3615650\ttotal: 270ms\tremaining: 1.05s\n204:\tlearn: 0.3612219\ttotal: 271ms\tremaining: 1.05s\n205:\tlearn: 0.3607920\ttotal: 272ms\tremaining: 1.05s\n206:\tlearn: 0.3604719\ttotal: 274ms\tremaining: 1.05s\n207:\tlearn: 0.3602678\ttotal: 275ms\tremaining: 1.05s\n208:\tlearn: 0.3600256\ttotal: 276ms\tremaining: 1.05s\n209:\tlearn: 0.3597211\ttotal: 278ms\tremaining: 1.04s\n210:\tlearn: 0.3593575\ttotal: 279ms\tremaining: 1.04s\n211:\tlearn: 0.3590378\ttotal: 280ms\tremaining: 1.04s\n212:\tlearn: 0.3589888\ttotal: 281ms\tremaining: 1.04s\n213:\tlearn: 0.3586668\ttotal: 283ms\tremaining: 1.04s\n214:\tlearn: 0.3586154\ttotal: 284ms\tremaining: 1.03s\n215:\tlearn: 0.3583470\ttotal: 285ms\tremaining: 1.03s\n216:\tlearn: 0.3581083\ttotal: 286ms\tremaining: 1.03s\n217:\tlearn: 0.3578125\ttotal: 288ms\tremaining: 1.03s\n218:\tlearn: 0.3574743\ttotal: 289ms\tremaining: 1.03s\n219:\tlearn: 0.3571345\ttotal: 291ms\tremaining: 1.03s\n220:\tlearn: 0.3568790\ttotal: 292ms\tremaining: 1.03s\n221:\tlearn: 0.3564717\ttotal: 293ms\tremaining: 1.03s\n222:\tlearn: 0.3560492\ttotal: 295ms\tremaining: 1.03s\n223:\tlearn: 0.3557979\ttotal: 296ms\tremaining: 1.02s\n224:\tlearn: 0.3555973\ttotal: 297ms\tremaining: 1.02s\n225:\tlearn: 0.3552493\ttotal: 299ms\tremaining: 1.02s\n226:\tlearn: 0.3550137\ttotal: 300ms\tremaining: 1.02s\n227:\tlearn: 0.3546823\ttotal: 302ms\tremaining: 1.02s\n228:\tlearn: 0.3543253\ttotal: 303ms\tremaining: 1.02s\n229:\tlearn: 0.3541066\ttotal: 304ms\tremaining: 1.02s\n230:\tlearn: 0.3538600\ttotal: 305ms\tremaining: 1.02s\n231:\tlearn: 0.3534868\ttotal: 307ms\tremaining: 1.01s\n232:\tlearn: 0.3531985\ttotal: 308ms\tremaining: 1.01s\n233:\tlearn: 0.3529198\ttotal: 310ms\tremaining: 1.01s\n234:\tlearn: 0.3526271\ttotal: 311ms\tremaining: 1.01s\n235:\tlearn: 0.3523048\ttotal: 312ms\tremaining: 1.01s\n236:\tlearn: 0.3520437\ttotal: 314ms\tremaining: 1.01s\n237:\tlearn: 0.3516882\ttotal: 315ms\tremaining: 1.01s\n238:\tlearn: 0.3514538\ttotal: 316ms\tremaining: 1.01s\n239:\tlearn: 0.3512176\ttotal: 317ms\tremaining: 1s\n240:\tlearn: 0.3509431\ttotal: 319ms\tremaining: 1s\n241:\tlearn: 0.3506362\ttotal: 320ms\tremaining: 1s\n242:\tlearn: 0.3503934\ttotal: 321ms\tremaining: 1s\n243:\tlearn: 0.3501993\ttotal: 323ms\tremaining: 999ms\n244:\tlearn: 0.3500023\ttotal: 324ms\tremaining: 998ms\n245:\tlearn: 0.3498073\ttotal: 325ms\tremaining: 997ms\n246:\tlearn: 0.3496334\ttotal: 326ms\tremaining: 995ms\n247:\tlearn: 0.3493233\ttotal: 328ms\tremaining: 994ms\n248:\tlearn: 0.3490207\ttotal: 329ms\tremaining: 992ms\n249:\tlearn: 0.3487930\ttotal: 330ms\tremaining: 991ms\n250:\tlearn: 0.3485273\ttotal: 332ms\tremaining: 989ms\n251:\tlearn: 0.3483183\ttotal: 333ms\tremaining: 988ms\n252:\tlearn: 0.3481449\ttotal: 334ms\tremaining: 987ms\n253:\tlearn: 0.3479113\ttotal: 335ms\tremaining: 985ms\n254:\tlearn: 0.3476127\ttotal: 337ms\tremaining: 984ms\n255:\tlearn: 0.3472854\ttotal: 338ms\tremaining: 982ms\n256:\tlearn: 0.3469425\ttotal: 339ms\tremaining: 981ms\n257:\tlearn: 0.3468701\ttotal: 340ms\tremaining: 979ms\n258:\tlearn: 0.3466920\ttotal: 342ms\tremaining: 978ms\n259:\tlearn: 0.3464607\ttotal: 343ms\tremaining: 976ms\n260:\tlearn: 0.3462171\ttotal: 344ms\tremaining: 975ms\n261:\tlearn: 0.3461673\ttotal: 345ms\tremaining: 973ms\n262:\tlearn: 0.3459325\ttotal: 347ms\tremaining: 971ms\n263:\tlearn: 0.3456664\ttotal: 348ms\tremaining: 970ms\n264:\tlearn: 0.3453805\ttotal: 349ms\tremaining: 969ms\n265:\tlearn: 0.3451982\ttotal: 351ms\tremaining: 967ms\n266:\tlearn: 0.3449740\ttotal: 352ms\tremaining: 966ms\n267:\tlearn: 0.3447986\ttotal: 353ms\tremaining: 964ms\n268:\tlearn: 0.3445476\ttotal: 354ms\tremaining: 963ms\n269:\tlearn: 0.3443443\ttotal: 356ms\tremaining: 962ms\n270:\tlearn: 0.3440121\ttotal: 357ms\tremaining: 960ms\n271:\tlearn: 0.3437523\ttotal: 358ms\tremaining: 959ms\n272:\tlearn: 0.3434180\ttotal: 360ms\tremaining: 957ms\n273:\tlearn: 0.3431703\ttotal: 361ms\tremaining: 956ms\n274:\tlearn: 0.3429551\ttotal: 362ms\tremaining: 955ms\n275:\tlearn: 0.3426571\ttotal: 364ms\tremaining: 954ms\n276:\tlearn: 0.3424543\ttotal: 365ms\tremaining: 953ms\n277:\tlearn: 0.3421855\ttotal: 366ms\tremaining: 951ms\n278:\tlearn: 0.3419199\ttotal: 368ms\tremaining: 950ms\n279:\tlearn: 0.3416234\ttotal: 369ms\tremaining: 949ms\n280:\tlearn: 0.3414410\ttotal: 370ms\tremaining: 947ms\n281:\tlearn: 0.3410844\ttotal: 372ms\tremaining: 946ms\n282:\tlearn: 0.3407167\ttotal: 374ms\tremaining: 948ms\n283:\tlearn: 0.3406982\ttotal: 376ms\tremaining: 947ms\n284:\tlearn: 0.3404485\ttotal: 377ms\tremaining: 946ms\n285:\tlearn: 0.3402440\ttotal: 378ms\tremaining: 944ms\n286:\tlearn: 0.3399089\ttotal: 380ms\tremaining: 943ms\n287:\tlearn: 0.3397277\ttotal: 381ms\tremaining: 942ms\n288:\tlearn: 0.3394403\ttotal: 382ms\tremaining: 940ms\n289:\tlearn: 0.3392802\ttotal: 383ms\tremaining: 939ms\n290:\tlearn: 0.3389966\ttotal: 385ms\tremaining: 938ms\n291:\tlearn: 0.3387269\ttotal: 386ms\tremaining: 936ms\n292:\tlearn: 0.3384379\ttotal: 387ms\tremaining: 935ms\n293:\tlearn: 0.3382130\ttotal: 389ms\tremaining: 934ms\n294:\tlearn: 0.3380097\ttotal: 390ms\tremaining: 933ms\n295:\tlearn: 0.3376649\ttotal: 392ms\tremaining: 932ms\n296:\tlearn: 0.3373943\ttotal: 393ms\tremaining: 931ms\n297:\tlearn: 0.3373692\ttotal: 394ms\tremaining: 928ms\n298:\tlearn: 0.3372242\ttotal: 395ms\tremaining: 927ms\n299:\tlearn: 0.3371052\ttotal: 397ms\tremaining: 926ms\n300:\tlearn: 0.3368458\ttotal: 398ms\tremaining: 924ms\n301:\tlearn: 0.3365440\ttotal: 399ms\tremaining: 923ms\n302:\tlearn: 0.3364032\ttotal: 401ms\tremaining: 922ms\n303:\tlearn: 0.3361169\ttotal: 402ms\tremaining: 921ms\n304:\tlearn: 0.3358718\ttotal: 403ms\tremaining: 919ms\n305:\tlearn: 0.3356318\ttotal: 405ms\tremaining: 918ms\n306:\tlearn: 0.3356035\ttotal: 406ms\tremaining: 916ms\n307:\tlearn: 0.3354056\ttotal: 407ms\tremaining: 914ms\n308:\tlearn: 0.3350256\ttotal: 408ms\tremaining: 913ms\n309:\tlearn: 0.3348244\ttotal: 410ms\tremaining: 912ms\n310:\tlearn: 0.3344690\ttotal: 411ms\tremaining: 910ms\n311:\tlearn: 0.3341631\ttotal: 412ms\tremaining: 909ms\n312:\tlearn: 0.3341294\ttotal: 413ms\tremaining: 907ms\n313:\tlearn: 0.3339216\ttotal: 415ms\tremaining: 906ms\n314:\tlearn: 0.3337193\ttotal: 416ms\tremaining: 904ms\n315:\tlearn: 0.3335134\ttotal: 417ms\tremaining: 903ms\n316:\tlearn: 0.3332284\ttotal: 418ms\tremaining: 901ms\n317:\tlearn: 0.3330645\ttotal: 420ms\tremaining: 900ms\n318:\tlearn: 0.3328726\ttotal: 421ms\tremaining: 899ms\n319:\tlearn: 0.3326566\ttotal: 422ms\tremaining: 897ms\n320:\tlearn: 0.3324417\ttotal: 424ms\tremaining: 896ms\n321:\tlearn: 0.3322102\ttotal: 425ms\tremaining: 894ms\n322:\tlearn: 0.3319472\ttotal: 426ms\tremaining: 893ms\n323:\tlearn: 0.3318250\ttotal: 427ms\tremaining: 892ms\n324:\tlearn: 0.3315776\ttotal: 429ms\tremaining: 890ms\n325:\tlearn: 0.3314118\ttotal: 430ms\tremaining: 889ms\n326:\tlearn: 0.3312500\ttotal: 431ms\tremaining: 888ms\n327:\tlearn: 0.3310297\ttotal: 432ms\tremaining: 886ms\n328:\tlearn: 0.3308546\ttotal: 434ms\tremaining: 885ms\n329:\tlearn: 0.3306564\ttotal: 435ms\tremaining: 883ms\n330:\tlearn: 0.3305563\ttotal: 436ms\tremaining: 881ms\n331:\tlearn: 0.3304758\ttotal: 437ms\tremaining: 880ms\n332:\tlearn: 0.3301638\ttotal: 438ms\tremaining: 878ms\n333:\tlearn: 0.3298371\ttotal: 440ms\tremaining: 877ms\n334:\tlearn: 0.3296341\ttotal: 441ms\tremaining: 875ms\n335:\tlearn: 0.3293369\ttotal: 442ms\tremaining: 874ms\n336:\tlearn: 0.3291061\ttotal: 443ms\tremaining: 872ms\n337:\tlearn: 0.3288663\ttotal: 445ms\tremaining: 871ms\n338:\tlearn: 0.3286668\ttotal: 446ms\tremaining: 869ms\n339:\tlearn: 0.3283135\ttotal: 447ms\tremaining: 868ms\n340:\tlearn: 0.3281119\ttotal: 448ms\tremaining: 867ms\n341:\tlearn: 0.3278855\ttotal: 450ms\tremaining: 865ms\n342:\tlearn: 0.3276559\ttotal: 451ms\tremaining: 864ms\n343:\tlearn: 0.3274257\ttotal: 452ms\tremaining: 862ms\n344:\tlearn: 0.3272050\ttotal: 453ms\tremaining: 861ms\n345:\tlearn: 0.3270119\ttotal: 455ms\tremaining: 859ms\n346:\tlearn: 0.3267618\ttotal: 456ms\tremaining: 858ms\n347:\tlearn: 0.3265265\ttotal: 457ms\tremaining: 857ms\n348:\tlearn: 0.3263297\ttotal: 459ms\tremaining: 855ms\n349:\tlearn: 0.3261416\ttotal: 460ms\tremaining: 854ms\n350:\tlearn: 0.3258940\ttotal: 461ms\tremaining: 853ms\n351:\tlearn: 0.3257441\ttotal: 462ms\tremaining: 851ms\n352:\tlearn: 0.3257247\ttotal: 463ms\tremaining: 849ms\n353:\tlearn: 0.3255059\ttotal: 465ms\tremaining: 848ms\n354:\tlearn: 0.3253445\ttotal: 466ms\tremaining: 847ms\n355:\tlearn: 0.3250101\ttotal: 467ms\tremaining: 845ms\n356:\tlearn: 0.3248142\ttotal: 469ms\tremaining: 844ms\n357:\tlearn: 0.3246638\ttotal: 470ms\tremaining: 842ms\n358:\tlearn: 0.3245202\ttotal: 471ms\tremaining: 841ms\n359:\tlearn: 0.3242119\ttotal: 472ms\tremaining: 840ms\n360:\tlearn: 0.3239574\ttotal: 474ms\tremaining: 838ms\n361:\tlearn: 0.3237838\ttotal: 475ms\tremaining: 837ms\n362:\tlearn: 0.3235004\ttotal: 476ms\tremaining: 836ms\n363:\tlearn: 0.3232922\ttotal: 477ms\tremaining: 834ms\n364:\tlearn: 0.3230232\ttotal: 479ms\tremaining: 833ms\n365:\tlearn: 0.3228873\ttotal: 480ms\tremaining: 831ms\n366:\tlearn: 0.3227095\ttotal: 481ms\tremaining: 830ms\n367:\tlearn: 0.3225151\ttotal: 482ms\tremaining: 829ms\n368:\tlearn: 0.3223609\ttotal: 484ms\tremaining: 827ms\n369:\tlearn: 0.3221793\ttotal: 485ms\tremaining: 826ms\n370:\tlearn: 0.3219470\ttotal: 486ms\tremaining: 825ms\n371:\tlearn: 0.3217563\ttotal: 488ms\tremaining: 823ms\n372:\tlearn: 0.3215259\ttotal: 489ms\tremaining: 822ms\n373:\tlearn: 0.3213921\ttotal: 490ms\tremaining: 821ms\n374:\tlearn: 0.3212560\ttotal: 492ms\tremaining: 819ms\n375:\tlearn: 0.3209756\ttotal: 493ms\tremaining: 818ms\n376:\tlearn: 0.3208119\ttotal: 494ms\tremaining: 817ms\n377:\tlearn: 0.3205885\ttotal: 496ms\tremaining: 815ms\n378:\tlearn: 0.3205233\ttotal: 497ms\tremaining: 814ms\n379:\tlearn: 0.3203816\ttotal: 498ms\tremaining: 813ms\n380:\tlearn: 0.3202002\ttotal: 499ms\tremaining: 811ms\n381:\tlearn: 0.3200266\ttotal: 501ms\tremaining: 810ms\n382:\tlearn: 0.3198362\ttotal: 502ms\tremaining: 809ms\n383:\tlearn: 0.3195630\ttotal: 504ms\tremaining: 808ms\n384:\tlearn: 0.3194004\ttotal: 505ms\tremaining: 807ms\n385:\tlearn: 0.3192132\ttotal: 506ms\tremaining: 805ms\n386:\tlearn: 0.3190499\ttotal: 508ms\tremaining: 804ms\n387:\tlearn: 0.3188472\ttotal: 509ms\tremaining: 803ms\n388:\tlearn: 0.3186495\ttotal: 510ms\tremaining: 801ms\n389:\tlearn: 0.3184074\ttotal: 511ms\tremaining: 800ms\n390:\tlearn: 0.3181990\ttotal: 513ms\tremaining: 799ms\n391:\tlearn: 0.3180053\ttotal: 514ms\tremaining: 797ms\n392:\tlearn: 0.3176707\ttotal: 515ms\tremaining: 796ms\n393:\tlearn: 0.3175041\ttotal: 517ms\tremaining: 795ms\n394:\tlearn: 0.3173406\ttotal: 518ms\tremaining: 793ms\n395:\tlearn: 0.3172226\ttotal: 519ms\tremaining: 792ms\n396:\tlearn: 0.3170523\ttotal: 521ms\tremaining: 791ms\n397:\tlearn: 0.3168946\ttotal: 522ms\tremaining: 790ms\n398:\tlearn: 0.3166836\ttotal: 523ms\tremaining: 788ms\n399:\tlearn: 0.3165552\ttotal: 525ms\tremaining: 787ms\n400:\tlearn: 0.3163364\ttotal: 526ms\tremaining: 786ms\n401:\tlearn: 0.3162982\ttotal: 527ms\tremaining: 784ms\n402:\tlearn: 0.3160446\ttotal: 528ms\tremaining: 783ms\n403:\tlearn: 0.3157943\ttotal: 529ms\tremaining: 781ms\n404:\tlearn: 0.3157422\ttotal: 531ms\tremaining: 780ms\n405:\tlearn: 0.3155487\ttotal: 532ms\tremaining: 778ms\n406:\tlearn: 0.3153704\ttotal: 533ms\tremaining: 777ms\n407:\tlearn: 0.3151216\ttotal: 534ms\tremaining: 775ms\n408:\tlearn: 0.3149820\ttotal: 536ms\tremaining: 774ms\n409:\tlearn: 0.3147236\ttotal: 537ms\tremaining: 773ms\n410:\tlearn: 0.3145455\ttotal: 538ms\tremaining: 771ms\n411:\tlearn: 0.3144075\ttotal: 540ms\tremaining: 770ms\n412:\tlearn: 0.3143930\ttotal: 541ms\tremaining: 768ms\n413:\tlearn: 0.3142231\ttotal: 542ms\tremaining: 767ms\n414:\tlearn: 0.3139974\ttotal: 543ms\tremaining: 766ms\n415:\tlearn: 0.3138447\ttotal: 545ms\tremaining: 765ms\n416:\tlearn: 0.3136665\ttotal: 546ms\tremaining: 763ms\n417:\tlearn: 0.3134969\ttotal: 547ms\tremaining: 762ms\n418:\tlearn: 0.3132821\ttotal: 549ms\tremaining: 761ms\n419:\tlearn: 0.3131396\ttotal: 550ms\tremaining: 759ms\n420:\tlearn: 0.3129509\ttotal: 551ms\tremaining: 758ms\n421:\tlearn: 0.3128049\ttotal: 552ms\tremaining: 757ms\n422:\tlearn: 0.3126810\ttotal: 554ms\tremaining: 755ms\n423:\tlearn: 0.3125379\ttotal: 555ms\tremaining: 754ms\n424:\tlearn: 0.3124673\ttotal: 556ms\tremaining: 752ms\n425:\tlearn: 0.3123075\ttotal: 557ms\tremaining: 751ms\n426:\tlearn: 0.3121999\ttotal: 559ms\tremaining: 750ms\n427:\tlearn: 0.3120471\ttotal: 560ms\tremaining: 748ms\n428:\tlearn: 0.3118661\ttotal: 561ms\tremaining: 747ms\n429:\tlearn: 0.3116159\ttotal: 563ms\tremaining: 746ms\n430:\tlearn: 0.3114321\ttotal: 564ms\tremaining: 745ms\n431:\tlearn: 0.3112992\ttotal: 565ms\tremaining: 743ms\n432:\tlearn: 0.3111575\ttotal: 567ms\tremaining: 742ms\n433:\tlearn: 0.3109582\ttotal: 568ms\tremaining: 741ms\n434:\tlearn: 0.3107156\ttotal: 569ms\tremaining: 739ms\n435:\tlearn: 0.3104343\ttotal: 571ms\tremaining: 738ms\n436:\tlearn: 0.3102203\ttotal: 572ms\tremaining: 737ms\n437:\tlearn: 0.3100993\ttotal: 574ms\tremaining: 736ms\n438:\tlearn: 0.3100899\ttotal: 575ms\tremaining: 734ms\n439:\tlearn: 0.3098086\ttotal: 576ms\tremaining: 733ms\n440:\tlearn: 0.3095925\ttotal: 577ms\tremaining: 732ms\n441:\tlearn: 0.3093341\ttotal: 579ms\tremaining: 731ms\n442:\tlearn: 0.3091640\ttotal: 580ms\tremaining: 729ms\n443:\tlearn: 0.3089960\ttotal: 581ms\tremaining: 728ms\n444:\tlearn: 0.3089066\ttotal: 583ms\tremaining: 727ms\n445:\tlearn: 0.3087554\ttotal: 584ms\tremaining: 725ms\n446:\tlearn: 0.3086161\ttotal: 585ms\tremaining: 724ms\n447:\tlearn: 0.3083538\ttotal: 587ms\tremaining: 723ms\n448:\tlearn: 0.3082217\ttotal: 588ms\tremaining: 721ms\n449:\tlearn: 0.3080326\ttotal: 589ms\tremaining: 720ms\n450:\tlearn: 0.3080118\ttotal: 590ms\tremaining: 718ms\n451:\tlearn: 0.3077435\ttotal: 591ms\tremaining: 717ms\n452:\tlearn: 0.3075747\ttotal: 593ms\tremaining: 716ms\n453:\tlearn: 0.3073330\ttotal: 594ms\tremaining: 714ms\n454:\tlearn: 0.3071039\ttotal: 595ms\tremaining: 713ms\n455:\tlearn: 0.3069636\ttotal: 597ms\tremaining: 712ms\n456:\tlearn: 0.3067937\ttotal: 598ms\tremaining: 710ms\n457:\tlearn: 0.3066205\ttotal: 599ms\tremaining: 709ms\n458:\tlearn: 0.3064745\ttotal: 601ms\tremaining: 708ms\n459:\tlearn: 0.3061776\ttotal: 602ms\tremaining: 706ms\n460:\tlearn: 0.3059923\ttotal: 603ms\tremaining: 705ms\n461:\tlearn: 0.3058502\ttotal: 605ms\tremaining: 704ms\n462:\tlearn: 0.3056956\ttotal: 606ms\tremaining: 703ms\n463:\tlearn: 0.3055300\ttotal: 607ms\tremaining: 701ms\n464:\tlearn: 0.3053668\ttotal: 609ms\tremaining: 700ms\n465:\tlearn: 0.3052509\ttotal: 610ms\tremaining: 699ms\n466:\tlearn: 0.3051311\ttotal: 611ms\tremaining: 697ms\n467:\tlearn: 0.3049717\ttotal: 612ms\tremaining: 696ms\n468:\tlearn: 0.3046705\ttotal: 614ms\tremaining: 695ms\n469:\tlearn: 0.3044311\ttotal: 615ms\tremaining: 694ms\n470:\tlearn: 0.3042926\ttotal: 616ms\tremaining: 692ms\n471:\tlearn: 0.3040725\ttotal: 618ms\tremaining: 691ms\n472:\tlearn: 0.3038213\ttotal: 619ms\tremaining: 690ms\n473:\tlearn: 0.3036048\ttotal: 620ms\tremaining: 688ms\n474:\tlearn: 0.3034112\ttotal: 621ms\tremaining: 687ms\n475:\tlearn: 0.3032099\ttotal: 623ms\tremaining: 685ms\n476:\tlearn: 0.3030166\ttotal: 624ms\tremaining: 684ms\n477:\tlearn: 0.3028528\ttotal: 625ms\tremaining: 683ms\n478:\tlearn: 0.3026546\ttotal: 626ms\tremaining: 681ms\n479:\tlearn: 0.3025205\ttotal: 628ms\tremaining: 680ms\n480:\tlearn: 0.3023115\ttotal: 629ms\tremaining: 679ms\n481:\tlearn: 0.3020713\ttotal: 630ms\tremaining: 677ms\n482:\tlearn: 0.3019294\ttotal: 632ms\tremaining: 676ms\n483:\tlearn: 0.3017173\ttotal: 633ms\tremaining: 675ms\n484:\tlearn: 0.3015662\ttotal: 634ms\tremaining: 673ms\n485:\tlearn: 0.3014400\ttotal: 635ms\tremaining: 672ms\n486:\tlearn: 0.3011866\ttotal: 637ms\tremaining: 671ms\n487:\tlearn: 0.3010180\ttotal: 638ms\tremaining: 669ms\n488:\tlearn: 0.3008270\ttotal: 639ms\tremaining: 668ms\n489:\tlearn: 0.3006188\ttotal: 641ms\tremaining: 667ms\n490:\tlearn: 0.3004381\ttotal: 642ms\tremaining: 665ms\n491:\tlearn: 0.3002576\ttotal: 643ms\tremaining: 664ms\n492:\tlearn: 0.3001035\ttotal: 645ms\tremaining: 663ms\n493:\tlearn: 0.2999499\ttotal: 646ms\tremaining: 662ms\n494:\tlearn: 0.2998038\ttotal: 647ms\tremaining: 660ms\n495:\tlearn: 0.2996552\ttotal: 649ms\tremaining: 659ms\n496:\tlearn: 0.2995609\ttotal: 650ms\tremaining: 658ms\n497:\tlearn: 0.2993399\ttotal: 651ms\tremaining: 656ms\n498:\tlearn: 0.2991290\ttotal: 653ms\tremaining: 655ms\n499:\tlearn: 0.2989929\ttotal: 654ms\tremaining: 654ms\n500:\tlearn: 0.2988133\ttotal: 655ms\tremaining: 653ms\n501:\tlearn: 0.2988077\ttotal: 656ms\tremaining: 651ms\n502:\tlearn: 0.2986237\ttotal: 658ms\tremaining: 650ms\n503:\tlearn: 0.2985032\ttotal: 659ms\tremaining: 649ms\n504:\tlearn: 0.2983225\ttotal: 661ms\tremaining: 648ms\n505:\tlearn: 0.2981938\ttotal: 662ms\tremaining: 646ms\n506:\tlearn: 0.2980074\ttotal: 664ms\tremaining: 645ms\n507:\tlearn: 0.2978381\ttotal: 665ms\tremaining: 644ms\n508:\tlearn: 0.2975839\ttotal: 666ms\tremaining: 643ms\n509:\tlearn: 0.2974784\ttotal: 668ms\tremaining: 642ms\n510:\tlearn: 0.2972939\ttotal: 669ms\tremaining: 640ms\n511:\tlearn: 0.2971314\ttotal: 670ms\tremaining: 639ms\n512:\tlearn: 0.2968813\ttotal: 672ms\tremaining: 638ms\n513:\tlearn: 0.2967325\ttotal: 673ms\tremaining: 636ms\n514:\tlearn: 0.2965454\ttotal: 674ms\tremaining: 635ms\n515:\tlearn: 0.2962539\ttotal: 676ms\tremaining: 634ms\n516:\tlearn: 0.2960436\ttotal: 677ms\tremaining: 632ms\n517:\tlearn: 0.2959016\ttotal: 678ms\tremaining: 631ms\n518:\tlearn: 0.2957332\ttotal: 679ms\tremaining: 630ms\n519:\tlearn: 0.2955595\ttotal: 681ms\tremaining: 628ms\n520:\tlearn: 0.2953197\ttotal: 682ms\tremaining: 627ms\n521:\tlearn: 0.2951845\ttotal: 683ms\tremaining: 626ms\n522:\tlearn: 0.2950628\ttotal: 684ms\tremaining: 624ms\n523:\tlearn: 0.2949075\ttotal: 686ms\tremaining: 623ms\n524:\tlearn: 0.2947625\ttotal: 687ms\tremaining: 621ms\n525:\tlearn: 0.2946216\ttotal: 688ms\tremaining: 620ms\n526:\tlearn: 0.2945147\ttotal: 689ms\tremaining: 619ms\n527:\tlearn: 0.2942964\ttotal: 691ms\tremaining: 617ms\n528:\tlearn: 0.2941423\ttotal: 692ms\tremaining: 616ms\n529:\tlearn: 0.2939525\ttotal: 694ms\tremaining: 615ms\n530:\tlearn: 0.2937412\ttotal: 695ms\tremaining: 614ms\n531:\tlearn: 0.2935794\ttotal: 696ms\tremaining: 612ms\n532:\tlearn: 0.2932461\ttotal: 697ms\tremaining: 611ms\n533:\tlearn: 0.2930485\ttotal: 699ms\tremaining: 610ms\n534:\tlearn: 0.2929229\ttotal: 700ms\tremaining: 608ms\n535:\tlearn: 0.2927446\ttotal: 701ms\tremaining: 607ms\n536:\tlearn: 0.2925726\ttotal: 703ms\tremaining: 606ms\n537:\tlearn: 0.2923360\ttotal: 704ms\tremaining: 604ms\n538:\tlearn: 0.2922029\ttotal: 705ms\tremaining: 603ms\n539:\tlearn: 0.2920647\ttotal: 707ms\tremaining: 602ms\n540:\tlearn: 0.2919557\ttotal: 708ms\tremaining: 601ms\n541:\tlearn: 0.2917632\ttotal: 709ms\tremaining: 599ms\n542:\tlearn: 0.2915359\ttotal: 711ms\tremaining: 598ms\n543:\tlearn: 0.2913527\ttotal: 712ms\tremaining: 597ms\n544:\tlearn: 0.2911830\ttotal: 713ms\tremaining: 595ms\n545:\tlearn: 0.2909596\ttotal: 714ms\tremaining: 594ms\n546:\tlearn: 0.2908098\ttotal: 716ms\tremaining: 593ms\n547:\tlearn: 0.2906936\ttotal: 717ms\tremaining: 591ms\n548:\tlearn: 0.2905236\ttotal: 718ms\tremaining: 590ms\n549:\tlearn: 0.2903478\ttotal: 719ms\tremaining: 589ms\n550:\tlearn: 0.2902190\ttotal: 721ms\tremaining: 587ms\n551:\tlearn: 0.2900984\ttotal: 722ms\tremaining: 586ms\n552:\tlearn: 0.2898902\ttotal: 723ms\tremaining: 585ms\n553:\tlearn: 0.2897362\ttotal: 724ms\tremaining: 583ms\n554:\tlearn: 0.2895528\ttotal: 726ms\tremaining: 582ms\n555:\tlearn: 0.2893705\ttotal: 727ms\tremaining: 581ms\n556:\tlearn: 0.2891897\ttotal: 728ms\tremaining: 579ms\n557:\tlearn: 0.2890448\ttotal: 730ms\tremaining: 578ms\n558:\tlearn: 0.2889301\ttotal: 731ms\tremaining: 577ms\n559:\tlearn: 0.2887452\ttotal: 733ms\tremaining: 576ms\n560:\tlearn: 0.2885873\ttotal: 734ms\tremaining: 574ms\n561:\tlearn: 0.2884275\ttotal: 735ms\tremaining: 573ms\n562:\tlearn: 0.2881778\ttotal: 737ms\tremaining: 572ms\n563:\tlearn: 0.2880175\ttotal: 738ms\tremaining: 570ms\n564:\tlearn: 0.2878475\ttotal: 739ms\tremaining: 569ms\n565:\tlearn: 0.2877268\ttotal: 741ms\tremaining: 568ms\n566:\tlearn: 0.2875861\ttotal: 742ms\tremaining: 567ms\n567:\tlearn: 0.2874348\ttotal: 743ms\tremaining: 565ms\n568:\tlearn: 0.2872822\ttotal: 744ms\tremaining: 564ms\n569:\tlearn: 0.2870548\ttotal: 746ms\tremaining: 563ms\n570:\tlearn: 0.2867685\ttotal: 747ms\tremaining: 561ms\n571:\tlearn: 0.2866067\ttotal: 750ms\tremaining: 561ms\n572:\tlearn: 0.2864157\ttotal: 751ms\tremaining: 560ms\n573:\tlearn: 0.2864108\ttotal: 752ms\tremaining: 558ms\n574:\tlearn: 0.2862589\ttotal: 754ms\tremaining: 557ms\n575:\tlearn: 0.2861226\ttotal: 755ms\tremaining: 556ms\n576:\tlearn: 0.2858864\ttotal: 756ms\tremaining: 555ms\n577:\tlearn: 0.2857049\ttotal: 758ms\tremaining: 553ms\n578:\tlearn: 0.2854759\ttotal: 759ms\tremaining: 552ms\n579:\tlearn: 0.2854682\ttotal: 760ms\tremaining: 550ms\n580:\tlearn: 0.2852976\ttotal: 761ms\tremaining: 549ms\n581:\tlearn: 0.2851420\ttotal: 763ms\tremaining: 548ms\n582:\tlearn: 0.2850045\ttotal: 764ms\tremaining: 546ms\n583:\tlearn: 0.2847854\ttotal: 765ms\tremaining: 545ms\n584:\tlearn: 0.2844940\ttotal: 767ms\tremaining: 544ms\n585:\tlearn: 0.2842732\ttotal: 768ms\tremaining: 543ms\n586:\tlearn: 0.2841619\ttotal: 770ms\tremaining: 542ms\n587:\tlearn: 0.2839890\ttotal: 771ms\tremaining: 540ms\n588:\tlearn: 0.2838209\ttotal: 772ms\tremaining: 539ms\n589:\tlearn: 0.2836811\ttotal: 774ms\tremaining: 538ms\n590:\tlearn: 0.2835101\ttotal: 775ms\tremaining: 536ms\n591:\tlearn: 0.2833723\ttotal: 776ms\tremaining: 535ms\n592:\tlearn: 0.2831506\ttotal: 777ms\tremaining: 534ms\n593:\tlearn: 0.2829968\ttotal: 779ms\tremaining: 532ms\n594:\tlearn: 0.2828125\ttotal: 780ms\tremaining: 531ms\n595:\tlearn: 0.2826944\ttotal: 781ms\tremaining: 530ms\n596:\tlearn: 0.2824992\ttotal: 783ms\tremaining: 528ms\n597:\tlearn: 0.2822401\ttotal: 784ms\tremaining: 527ms\n598:\tlearn: 0.2819873\ttotal: 785ms\tremaining: 526ms\n599:\tlearn: 0.2817665\ttotal: 786ms\tremaining: 524ms\n600:\tlearn: 0.2815971\ttotal: 788ms\tremaining: 523ms\n601:\tlearn: 0.2814480\ttotal: 789ms\tremaining: 522ms\n602:\tlearn: 0.2811856\ttotal: 790ms\tremaining: 520ms\n603:\tlearn: 0.2810008\ttotal: 792ms\tremaining: 519ms\n604:\tlearn: 0.2807857\ttotal: 793ms\tremaining: 518ms\n605:\tlearn: 0.2806468\ttotal: 794ms\tremaining: 516ms\n606:\tlearn: 0.2805099\ttotal: 795ms\tremaining: 515ms\n607:\tlearn: 0.2803619\ttotal: 797ms\tremaining: 514ms\n608:\tlearn: 0.2801597\ttotal: 798ms\tremaining: 512ms\n609:\tlearn: 0.2800139\ttotal: 799ms\tremaining: 511ms\n610:\tlearn: 0.2798046\ttotal: 801ms\tremaining: 510ms\n611:\tlearn: 0.2796424\ttotal: 802ms\tremaining: 508ms\n612:\tlearn: 0.2794853\ttotal: 803ms\tremaining: 507ms\n613:\tlearn: 0.2792925\ttotal: 804ms\tremaining: 506ms\n614:\tlearn: 0.2791354\ttotal: 806ms\tremaining: 504ms\n615:\tlearn: 0.2789958\ttotal: 807ms\tremaining: 503ms\n616:\tlearn: 0.2788063\ttotal: 808ms\tremaining: 502ms\n617:\tlearn: 0.2786400\ttotal: 810ms\tremaining: 500ms\n618:\tlearn: 0.2785140\ttotal: 811ms\tremaining: 499ms\n619:\tlearn: 0.2783569\ttotal: 812ms\tremaining: 498ms\n620:\tlearn: 0.2781239\ttotal: 813ms\tremaining: 496ms\n621:\tlearn: 0.2781215\ttotal: 814ms\tremaining: 495ms\n622:\tlearn: 0.2779133\ttotal: 815ms\tremaining: 493ms\n623:\tlearn: 0.2777607\ttotal: 817ms\tremaining: 492ms\n624:\tlearn: 0.2775664\ttotal: 818ms\tremaining: 491ms\n625:\tlearn: 0.2774211\ttotal: 819ms\tremaining: 490ms\n626:\tlearn: 0.2772632\ttotal: 821ms\tremaining: 488ms\n627:\tlearn: 0.2770905\ttotal: 822ms\tremaining: 487ms\n628:\tlearn: 0.2769051\ttotal: 823ms\tremaining: 486ms\n629:\tlearn: 0.2767749\ttotal: 825ms\tremaining: 484ms\n630:\tlearn: 0.2765253\ttotal: 826ms\tremaining: 483ms\n631:\tlearn: 0.2763193\ttotal: 827ms\tremaining: 482ms\n632:\tlearn: 0.2760831\ttotal: 828ms\tremaining: 480ms\n633:\tlearn: 0.2759096\ttotal: 830ms\tremaining: 479ms\n634:\tlearn: 0.2757282\ttotal: 831ms\tremaining: 478ms\n635:\tlearn: 0.2755605\ttotal: 832ms\tremaining: 476ms\n636:\tlearn: 0.2754263\ttotal: 833ms\tremaining: 475ms\n637:\tlearn: 0.2752885\ttotal: 835ms\tremaining: 474ms\n638:\tlearn: 0.2751041\ttotal: 836ms\tremaining: 472ms\n639:\tlearn: 0.2749064\ttotal: 837ms\tremaining: 471ms\n640:\tlearn: 0.2746700\ttotal: 839ms\tremaining: 470ms\n641:\tlearn: 0.2745215\ttotal: 840ms\tremaining: 468ms\n642:\tlearn: 0.2744073\ttotal: 841ms\tremaining: 467ms\n643:\tlearn: 0.2742254\ttotal: 843ms\tremaining: 466ms\n644:\tlearn: 0.2740165\ttotal: 845ms\tremaining: 465ms\n645:\tlearn: 0.2739000\ttotal: 846ms\tremaining: 464ms\n646:\tlearn: 0.2737322\ttotal: 847ms\tremaining: 462ms\n647:\tlearn: 0.2735602\ttotal: 849ms\tremaining: 461ms\n648:\tlearn: 0.2734075\ttotal: 850ms\tremaining: 460ms\n649:\tlearn: 0.2732657\ttotal: 851ms\tremaining: 458ms\n650:\tlearn: 0.2731144\ttotal: 853ms\tremaining: 457ms\n651:\tlearn: 0.2729493\ttotal: 854ms\tremaining: 456ms\n652:\tlearn: 0.2727507\ttotal: 855ms\tremaining: 455ms\n653:\tlearn: 0.2725912\ttotal: 857ms\tremaining: 453ms\n654:\tlearn: 0.2724875\ttotal: 858ms\tremaining: 452ms\n655:\tlearn: 0.2723055\ttotal: 860ms\tremaining: 451ms\n656:\tlearn: 0.2721795\ttotal: 861ms\tremaining: 449ms\n657:\tlearn: 0.2720429\ttotal: 862ms\tremaining: 448ms\n658:\tlearn: 0.2718504\ttotal: 863ms\tremaining: 447ms\n659:\tlearn: 0.2717093\ttotal: 865ms\tremaining: 445ms\n660:\tlearn: 0.2715647\ttotal: 866ms\tremaining: 444ms\n661:\tlearn: 0.2714193\ttotal: 867ms\tremaining: 443ms\n662:\tlearn: 0.2712147\ttotal: 868ms\tremaining: 441ms\n663:\tlearn: 0.2710933\ttotal: 870ms\tremaining: 440ms\n664:\tlearn: 0.2708801\ttotal: 871ms\tremaining: 439ms\n665:\tlearn: 0.2707377\ttotal: 872ms\tremaining: 438ms\n666:\tlearn: 0.2705821\ttotal: 874ms\tremaining: 436ms\n667:\tlearn: 0.2704057\ttotal: 875ms\tremaining: 435ms\n668:\tlearn: 0.2702309\ttotal: 876ms\tremaining: 434ms\n669:\tlearn: 0.2700340\ttotal: 878ms\tremaining: 432ms\n670:\tlearn: 0.2698945\ttotal: 879ms\tremaining: 431ms\n671:\tlearn: 0.2697308\ttotal: 880ms\tremaining: 430ms\n672:\tlearn: 0.2695605\ttotal: 881ms\tremaining: 428ms\n673:\tlearn: 0.2693502\ttotal: 883ms\tremaining: 427ms\n674:\tlearn: 0.2692143\ttotal: 884ms\tremaining: 426ms\n675:\tlearn: 0.2690329\ttotal: 885ms\tremaining: 424ms\n676:\tlearn: 0.2688854\ttotal: 887ms\tremaining: 423ms\n677:\tlearn: 0.2687502\ttotal: 888ms\tremaining: 422ms\n678:\tlearn: 0.2686358\ttotal: 889ms\tremaining: 420ms\n679:\tlearn: 0.2685010\ttotal: 890ms\tremaining: 419ms\n680:\tlearn: 0.2683418\ttotal: 892ms\tremaining: 418ms\n681:\tlearn: 0.2682146\ttotal: 893ms\tremaining: 416ms\n682:\tlearn: 0.2680718\ttotal: 894ms\tremaining: 415ms\n683:\tlearn: 0.2679366\ttotal: 895ms\tremaining: 414ms\n684:\tlearn: 0.2677370\ttotal: 897ms\tremaining: 412ms\n685:\tlearn: 0.2675566\ttotal: 898ms\tremaining: 411ms\n686:\tlearn: 0.2673894\ttotal: 900ms\tremaining: 410ms\n687:\tlearn: 0.2672498\ttotal: 901ms\tremaining: 409ms\n688:\tlearn: 0.2671363\ttotal: 902ms\tremaining: 407ms\n689:\tlearn: 0.2670043\ttotal: 903ms\tremaining: 406ms\n690:\tlearn: 0.2668368\ttotal: 905ms\tremaining: 405ms\n691:\tlearn: 0.2666707\ttotal: 906ms\tremaining: 403ms\n692:\tlearn: 0.2665714\ttotal: 907ms\tremaining: 402ms\n693:\tlearn: 0.2664364\ttotal: 909ms\tremaining: 401ms\n694:\tlearn: 0.2662776\ttotal: 910ms\tremaining: 399ms\n695:\tlearn: 0.2661164\ttotal: 911ms\tremaining: 398ms\n696:\tlearn: 0.2659506\ttotal: 913ms\tremaining: 397ms\n697:\tlearn: 0.2658006\ttotal: 914ms\tremaining: 395ms\n698:\tlearn: 0.2656033\ttotal: 915ms\tremaining: 394ms\n699:\tlearn: 0.2654248\ttotal: 916ms\tremaining: 393ms\n700:\tlearn: 0.2652839\ttotal: 918ms\tremaining: 391ms\n701:\tlearn: 0.2651159\ttotal: 919ms\tremaining: 390ms\n702:\tlearn: 0.2649314\ttotal: 920ms\tremaining: 389ms\n703:\tlearn: 0.2647537\ttotal: 922ms\tremaining: 388ms\n704:\tlearn: 0.2646088\ttotal: 923ms\tremaining: 386ms\n705:\tlearn: 0.2644970\ttotal: 925ms\tremaining: 385ms\n706:\tlearn: 0.2643188\ttotal: 926ms\tremaining: 384ms\n707:\tlearn: 0.2641252\ttotal: 927ms\tremaining: 382ms\n708:\tlearn: 0.2640359\ttotal: 929ms\tremaining: 381ms\n709:\tlearn: 0.2639199\ttotal: 930ms\tremaining: 380ms\n710:\tlearn: 0.2637750\ttotal: 931ms\tremaining: 378ms\n711:\tlearn: 0.2635847\ttotal: 932ms\tremaining: 377ms\n712:\tlearn: 0.2633960\ttotal: 934ms\tremaining: 376ms\n713:\tlearn: 0.2632343\ttotal: 935ms\tremaining: 375ms\n714:\tlearn: 0.2630984\ttotal: 937ms\tremaining: 373ms\n715:\tlearn: 0.2629790\ttotal: 938ms\tremaining: 372ms\n716:\tlearn: 0.2628442\ttotal: 940ms\tremaining: 371ms\n717:\tlearn: 0.2626876\ttotal: 941ms\tremaining: 370ms\n718:\tlearn: 0.2624853\ttotal: 942ms\tremaining: 368ms\n719:\tlearn: 0.2623398\ttotal: 944ms\tremaining: 367ms\n720:\tlearn: 0.2622274\ttotal: 945ms\tremaining: 366ms\n721:\tlearn: 0.2619933\ttotal: 946ms\tremaining: 364ms\n722:\tlearn: 0.2618562\ttotal: 948ms\tremaining: 363ms\n723:\tlearn: 0.2616724\ttotal: 949ms\tremaining: 362ms\n724:\tlearn: 0.2615328\ttotal: 951ms\tremaining: 361ms\n725:\tlearn: 0.2613417\ttotal: 952ms\tremaining: 359ms\n726:\tlearn: 0.2612160\ttotal: 953ms\tremaining: 358ms\n727:\tlearn: 0.2610727\ttotal: 955ms\tremaining: 357ms\n728:\tlearn: 0.2609397\ttotal: 956ms\tremaining: 355ms\n729:\tlearn: 0.2608150\ttotal: 958ms\tremaining: 354ms\n730:\tlearn: 0.2606940\ttotal: 959ms\tremaining: 353ms\n731:\tlearn: 0.2605297\ttotal: 960ms\tremaining: 352ms\n732:\tlearn: 0.2603439\ttotal: 961ms\tremaining: 350ms\n733:\tlearn: 0.2602117\ttotal: 963ms\tremaining: 349ms\n734:\tlearn: 0.2600208\ttotal: 964ms\tremaining: 348ms\n735:\tlearn: 0.2599040\ttotal: 965ms\tremaining: 346ms\n736:\tlearn: 0.2597566\ttotal: 967ms\tremaining: 345ms\n737:\tlearn: 0.2596297\ttotal: 968ms\tremaining: 344ms\n738:\tlearn: 0.2595039\ttotal: 969ms\tremaining: 342ms\n739:\tlearn: 0.2593529\ttotal: 970ms\tremaining: 341ms\n740:\tlearn: 0.2591722\ttotal: 972ms\tremaining: 340ms\n741:\tlearn: 0.2589801\ttotal: 973ms\tremaining: 338ms\n742:\tlearn: 0.2587950\ttotal: 974ms\tremaining: 337ms\n743:\tlearn: 0.2586596\ttotal: 976ms\tremaining: 336ms\n744:\tlearn: 0.2585278\ttotal: 977ms\tremaining: 334ms\n745:\tlearn: 0.2584181\ttotal: 978ms\tremaining: 333ms\n746:\tlearn: 0.2582351\ttotal: 980ms\tremaining: 332ms\n747:\tlearn: 0.2580539\ttotal: 981ms\tremaining: 331ms\n748:\tlearn: 0.2578629\ttotal: 982ms\tremaining: 329ms\n749:\tlearn: 0.2576646\ttotal: 984ms\tremaining: 328ms\n750:\tlearn: 0.2575551\ttotal: 985ms\tremaining: 327ms\n751:\tlearn: 0.2573615\ttotal: 986ms\tremaining: 325ms\n752:\tlearn: 0.2571761\ttotal: 987ms\tremaining: 324ms\n753:\tlearn: 0.2569959\ttotal: 989ms\tremaining: 323ms\n754:\tlearn: 0.2568631\ttotal: 990ms\tremaining: 321ms\n755:\tlearn: 0.2566885\ttotal: 991ms\tremaining: 320ms\n756:\tlearn: 0.2565213\ttotal: 993ms\tremaining: 319ms\n757:\tlearn: 0.2563737\ttotal: 994ms\tremaining: 317ms\n758:\tlearn: 0.2561886\ttotal: 996ms\tremaining: 316ms\n759:\tlearn: 0.2560190\ttotal: 997ms\tremaining: 315ms\n760:\tlearn: 0.2558421\ttotal: 998ms\tremaining: 314ms\n761:\tlearn: 0.2557115\ttotal: 1000ms\tremaining: 312ms\n762:\tlearn: 0.2555401\ttotal: 1s\tremaining: 311ms\n763:\tlearn: 0.2553786\ttotal: 1s\tremaining: 310ms\n764:\tlearn: 0.2551915\ttotal: 1s\tremaining: 309ms\n765:\tlearn: 0.2550035\ttotal: 1.01s\tremaining: 307ms\n766:\tlearn: 0.2548237\ttotal: 1.01s\tremaining: 306ms\n767:\tlearn: 0.2547038\ttotal: 1.01s\tremaining: 305ms\n768:\tlearn: 0.2545564\ttotal: 1.01s\tremaining: 304ms\n769:\tlearn: 0.2544045\ttotal: 1.01s\tremaining: 302ms\n770:\tlearn: 0.2542303\ttotal: 1.01s\tremaining: 301ms\n771:\tlearn: 0.2540661\ttotal: 1.01s\tremaining: 300ms\n772:\tlearn: 0.2539300\ttotal: 1.02s\tremaining: 298ms\n773:\tlearn: 0.2538359\ttotal: 1.02s\tremaining: 297ms\n774:\tlearn: 0.2536568\ttotal: 1.02s\tremaining: 296ms\n775:\tlearn: 0.2534452\ttotal: 1.02s\tremaining: 295ms\n776:\tlearn: 0.2533192\ttotal: 1.02s\tremaining: 293ms\n777:\tlearn: 0.2531626\ttotal: 1.02s\tremaining: 292ms\n778:\tlearn: 0.2529962\ttotal: 1.02s\tremaining: 291ms\n779:\tlearn: 0.2528201\ttotal: 1.02s\tremaining: 289ms\n780:\tlearn: 0.2526695\ttotal: 1.03s\tremaining: 288ms\n781:\tlearn: 0.2525457\ttotal: 1.03s\tremaining: 287ms\n782:\tlearn: 0.2523864\ttotal: 1.03s\tremaining: 285ms\n783:\tlearn: 0.2521857\ttotal: 1.03s\tremaining: 284ms\n784:\tlearn: 0.2520758\ttotal: 1.03s\tremaining: 283ms\n785:\tlearn: 0.2519207\ttotal: 1.03s\tremaining: 281ms\n786:\tlearn: 0.2517888\ttotal: 1.03s\tremaining: 280ms\n787:\tlearn: 0.2516184\ttotal: 1.04s\tremaining: 279ms\n788:\tlearn: 0.2514765\ttotal: 1.04s\tremaining: 278ms\n789:\tlearn: 0.2512973\ttotal: 1.04s\tremaining: 276ms\n790:\tlearn: 0.2511322\ttotal: 1.04s\tremaining: 275ms\n791:\tlearn: 0.2510109\ttotal: 1.04s\tremaining: 274ms\n792:\tlearn: 0.2508819\ttotal: 1.04s\tremaining: 273ms\n793:\tlearn: 0.2507410\ttotal: 1.04s\tremaining: 271ms\n794:\tlearn: 0.2506057\ttotal: 1.05s\tremaining: 270ms\n795:\tlearn: 0.2504359\ttotal: 1.05s\tremaining: 269ms\n796:\tlearn: 0.2502848\ttotal: 1.05s\tremaining: 268ms\n797:\tlearn: 0.2501274\ttotal: 1.05s\tremaining: 266ms\n798:\tlearn: 0.2499878\ttotal: 1.05s\tremaining: 265ms\n799:\tlearn: 0.2498258\ttotal: 1.05s\tremaining: 264ms\n800:\tlearn: 0.2496946\ttotal: 1.06s\tremaining: 262ms\n801:\tlearn: 0.2495761\ttotal: 1.06s\tremaining: 261ms\n802:\tlearn: 0.2494644\ttotal: 1.06s\tremaining: 260ms\n803:\tlearn: 0.2493376\ttotal: 1.06s\tremaining: 259ms\n804:\tlearn: 0.2491850\ttotal: 1.06s\tremaining: 257ms\n805:\tlearn: 0.2490135\ttotal: 1.06s\tremaining: 256ms\n806:\tlearn: 0.2488999\ttotal: 1.06s\tremaining: 255ms\n807:\tlearn: 0.2487890\ttotal: 1.07s\tremaining: 253ms\n808:\tlearn: 0.2486602\ttotal: 1.07s\tremaining: 252ms\n809:\tlearn: 0.2485331\ttotal: 1.07s\tremaining: 251ms\n810:\tlearn: 0.2483890\ttotal: 1.07s\tremaining: 249ms\n811:\tlearn: 0.2482359\ttotal: 1.07s\tremaining: 248ms\n812:\tlearn: 0.2481331\ttotal: 1.07s\tremaining: 247ms\n813:\tlearn: 0.2480208\ttotal: 1.07s\tremaining: 246ms\n814:\tlearn: 0.2478257\ttotal: 1.08s\tremaining: 244ms\n815:\tlearn: 0.2477161\ttotal: 1.08s\tremaining: 243ms\n816:\tlearn: 0.2476005\ttotal: 1.08s\tremaining: 242ms\n817:\tlearn: 0.2474556\ttotal: 1.08s\tremaining: 241ms\n818:\tlearn: 0.2473117\ttotal: 1.08s\tremaining: 239ms\n819:\tlearn: 0.2471438\ttotal: 1.08s\tremaining: 238ms\n820:\tlearn: 0.2470110\ttotal: 1.08s\tremaining: 237ms\n821:\tlearn: 0.2468662\ttotal: 1.09s\tremaining: 235ms\n822:\tlearn: 0.2466892\ttotal: 1.09s\tremaining: 234ms\n823:\tlearn: 0.2465174\ttotal: 1.09s\tremaining: 233ms\n824:\tlearn: 0.2463537\ttotal: 1.09s\tremaining: 232ms\n825:\tlearn: 0.2462154\ttotal: 1.09s\tremaining: 230ms\n826:\tlearn: 0.2460792\ttotal: 1.09s\tremaining: 229ms\n827:\tlearn: 0.2459665\ttotal: 1.09s\tremaining: 228ms\n828:\tlearn: 0.2458265\ttotal: 1.1s\tremaining: 226ms\n829:\tlearn: 0.2456899\ttotal: 1.1s\tremaining: 225ms\n830:\tlearn: 0.2455170\ttotal: 1.1s\tremaining: 224ms\n831:\tlearn: 0.2453429\ttotal: 1.1s\tremaining: 222ms\n832:\tlearn: 0.2452208\ttotal: 1.1s\tremaining: 221ms\n833:\tlearn: 0.2451141\ttotal: 1.1s\tremaining: 220ms\n834:\tlearn: 0.2449364\ttotal: 1.1s\tremaining: 218ms\n835:\tlearn: 0.2447844\ttotal: 1.1s\tremaining: 217ms\n836:\tlearn: 0.2446251\ttotal: 1.11s\tremaining: 216ms\n837:\tlearn: 0.2444965\ttotal: 1.11s\tremaining: 214ms\n838:\tlearn: 0.2443039\ttotal: 1.11s\tremaining: 213ms\n839:\tlearn: 0.2441645\ttotal: 1.11s\tremaining: 212ms\n840:\tlearn: 0.2440399\ttotal: 1.11s\tremaining: 210ms\n841:\tlearn: 0.2438619\ttotal: 1.11s\tremaining: 209ms\n842:\tlearn: 0.2437294\ttotal: 1.11s\tremaining: 208ms\n843:\tlearn: 0.2435935\ttotal: 1.12s\tremaining: 206ms\n844:\tlearn: 0.2434894\ttotal: 1.12s\tremaining: 205ms\n845:\tlearn: 0.2433041\ttotal: 1.12s\tremaining: 204ms\n846:\tlearn: 0.2431869\ttotal: 1.12s\tremaining: 203ms\n847:\tlearn: 0.2430468\ttotal: 1.12s\tremaining: 201ms\n848:\tlearn: 0.2428883\ttotal: 1.12s\tremaining: 200ms\n849:\tlearn: 0.2427056\ttotal: 1.13s\tremaining: 199ms\n850:\tlearn: 0.2425583\ttotal: 1.13s\tremaining: 197ms\n851:\tlearn: 0.2424505\ttotal: 1.13s\tremaining: 196ms\n852:\tlearn: 0.2423473\ttotal: 1.13s\tremaining: 195ms\n853:\tlearn: 0.2421961\ttotal: 1.13s\tremaining: 194ms\n854:\tlearn: 0.2420752\ttotal: 1.13s\tremaining: 192ms\n855:\tlearn: 0.2419252\ttotal: 1.14s\tremaining: 191ms\n856:\tlearn: 0.2417955\ttotal: 1.14s\tremaining: 190ms\n857:\tlearn: 0.2416949\ttotal: 1.14s\tremaining: 188ms\n858:\tlearn: 0.2415842\ttotal: 1.14s\tremaining: 187ms\n859:\tlearn: 0.2414533\ttotal: 1.14s\tremaining: 186ms\n860:\tlearn: 0.2413509\ttotal: 1.14s\tremaining: 185ms\n861:\tlearn: 0.2412500\ttotal: 1.14s\tremaining: 183ms\n862:\tlearn: 0.2411418\ttotal: 1.15s\tremaining: 182ms\n863:\tlearn: 0.2409877\ttotal: 1.15s\tremaining: 181ms\n864:\tlearn: 0.2408537\ttotal: 1.15s\tremaining: 179ms\n865:\tlearn: 0.2407417\ttotal: 1.15s\tremaining: 178ms\n866:\tlearn: 0.2406174\ttotal: 1.15s\tremaining: 177ms\n867:\tlearn: 0.2404251\ttotal: 1.15s\tremaining: 175ms\n868:\tlearn: 0.2402592\ttotal: 1.16s\tremaining: 174ms\n869:\tlearn: 0.2401515\ttotal: 1.16s\tremaining: 173ms\n870:\tlearn: 0.2400274\ttotal: 1.16s\tremaining: 171ms\n871:\tlearn: 0.2398506\ttotal: 1.16s\tremaining: 170ms\n872:\tlearn: 0.2397343\ttotal: 1.16s\tremaining: 169ms\n873:\tlearn: 0.2395966\ttotal: 1.16s\tremaining: 167ms\n874:\tlearn: 0.2394352\ttotal: 1.16s\tremaining: 166ms\n875:\tlearn: 0.2393079\ttotal: 1.16s\tremaining: 165ms\n876:\tlearn: 0.2392096\ttotal: 1.17s\tremaining: 164ms\n877:\tlearn: 0.2390577\ttotal: 1.17s\tremaining: 162ms\n878:\tlearn: 0.2389752\ttotal: 1.17s\tremaining: 161ms\n879:\tlearn: 0.2388773\ttotal: 1.17s\tremaining: 160ms\n880:\tlearn: 0.2387703\ttotal: 1.17s\tremaining: 158ms\n881:\tlearn: 0.2385955\ttotal: 1.17s\tremaining: 157ms\n882:\tlearn: 0.2384377\ttotal: 1.17s\tremaining: 156ms\n883:\tlearn: 0.2383398\ttotal: 1.18s\tremaining: 154ms\n884:\tlearn: 0.2381853\ttotal: 1.18s\tremaining: 153ms\n885:\tlearn: 0.2380371\ttotal: 1.18s\tremaining: 152ms\n886:\tlearn: 0.2379206\ttotal: 1.18s\tremaining: 150ms\n887:\tlearn: 0.2377223\ttotal: 1.18s\tremaining: 149ms\n888:\tlearn: 0.2376358\ttotal: 1.18s\tremaining: 148ms\n889:\tlearn: 0.2374768\ttotal: 1.18s\tremaining: 146ms\n890:\tlearn: 0.2373863\ttotal: 1.18s\tremaining: 145ms\n891:\tlearn: 0.2372932\ttotal: 1.19s\tremaining: 144ms\n892:\tlearn: 0.2371005\ttotal: 1.19s\tremaining: 142ms\n893:\tlearn: 0.2369937\ttotal: 1.19s\tremaining: 141ms\n894:\tlearn: 0.2368395\ttotal: 1.19s\tremaining: 140ms\n895:\tlearn: 0.2367441\ttotal: 1.19s\tremaining: 138ms\n896:\tlearn: 0.2366415\ttotal: 1.19s\tremaining: 137ms\n897:\tlearn: 0.2365279\ttotal: 1.19s\tremaining: 136ms\n898:\tlearn: 0.2363687\ttotal: 1.2s\tremaining: 134ms\n899:\tlearn: 0.2362222\ttotal: 1.2s\tremaining: 133ms\n900:\tlearn: 0.2361391\ttotal: 1.2s\tremaining: 132ms\n901:\tlearn: 0.2360159\ttotal: 1.2s\tremaining: 130ms\n902:\tlearn: 0.2359040\ttotal: 1.2s\tremaining: 129ms\n903:\tlearn: 0.2357487\ttotal: 1.2s\tremaining: 128ms\n904:\tlearn: 0.2356280\ttotal: 1.2s\tremaining: 126ms\n905:\tlearn: 0.2354862\ttotal: 1.2s\tremaining: 125ms\n906:\tlearn: 0.2352983\ttotal: 1.21s\tremaining: 124ms\n907:\tlearn: 0.2352044\ttotal: 1.21s\tremaining: 122ms\n908:\tlearn: 0.2350961\ttotal: 1.21s\tremaining: 121ms\n909:\tlearn: 0.2349078\ttotal: 1.21s\tremaining: 120ms\n910:\tlearn: 0.2348008\ttotal: 1.21s\tremaining: 118ms\n911:\tlearn: 0.2346816\ttotal: 1.21s\tremaining: 117ms\n912:\tlearn: 0.2345767\ttotal: 1.21s\tremaining: 116ms\n913:\tlearn: 0.2344968\ttotal: 1.21s\tremaining: 114ms\n914:\tlearn: 0.2344064\ttotal: 1.22s\tremaining: 113ms\n915:\tlearn: 0.2342559\ttotal: 1.22s\tremaining: 112ms\n916:\tlearn: 0.2340730\ttotal: 1.22s\tremaining: 110ms\n917:\tlearn: 0.2339523\ttotal: 1.22s\tremaining: 109ms\n918:\tlearn: 0.2337844\ttotal: 1.22s\tremaining: 108ms\n919:\tlearn: 0.2336549\ttotal: 1.22s\tremaining: 106ms\n920:\tlearn: 0.2335465\ttotal: 1.22s\tremaining: 105ms\n921:\tlearn: 0.2333997\ttotal: 1.23s\tremaining: 104ms\n922:\tlearn: 0.2332310\ttotal: 1.23s\tremaining: 102ms\n923:\tlearn: 0.2330662\ttotal: 1.23s\tremaining: 101ms\n924:\tlearn: 0.2329749\ttotal: 1.23s\tremaining: 99.7ms\n925:\tlearn: 0.2328288\ttotal: 1.23s\tremaining: 98.4ms\n926:\tlearn: 0.2327016\ttotal: 1.23s\tremaining: 97.1ms\n927:\tlearn: 0.2325844\ttotal: 1.23s\tremaining: 95.8ms\n928:\tlearn: 0.2324867\ttotal: 1.24s\tremaining: 94.4ms\n929:\tlearn: 0.2323499\ttotal: 1.24s\tremaining: 93.1ms\n930:\tlearn: 0.2321877\ttotal: 1.24s\tremaining: 91.8ms\n931:\tlearn: 0.2320211\ttotal: 1.24s\tremaining: 90.4ms\n932:\tlearn: 0.2318794\ttotal: 1.24s\tremaining: 89.1ms\n933:\tlearn: 0.2317919\ttotal: 1.24s\tremaining: 87.8ms\n934:\tlearn: 0.2316817\ttotal: 1.24s\tremaining: 86.4ms\n935:\tlearn: 0.2315785\ttotal: 1.24s\tremaining: 85.1ms\n936:\tlearn: 0.2314369\ttotal: 1.25s\tremaining: 83.8ms\n937:\tlearn: 0.2313316\ttotal: 1.25s\tremaining: 82.5ms\n938:\tlearn: 0.2311944\ttotal: 1.25s\tremaining: 81.1ms\n939:\tlearn: 0.2310629\ttotal: 1.25s\tremaining: 79.8ms\n940:\tlearn: 0.2308922\ttotal: 1.25s\tremaining: 78.5ms\n941:\tlearn: 0.2307811\ttotal: 1.25s\tremaining: 77.1ms\n942:\tlearn: 0.2306170\ttotal: 1.25s\tremaining: 75.8ms\n943:\tlearn: 0.2305289\ttotal: 1.25s\tremaining: 74.5ms\n944:\tlearn: 0.2303702\ttotal: 1.26s\tremaining: 73.2ms\n945:\tlearn: 0.2302684\ttotal: 1.26s\tremaining: 71.8ms\n946:\tlearn: 0.2300650\ttotal: 1.26s\tremaining: 70.5ms\n947:\tlearn: 0.2299574\ttotal: 1.26s\tremaining: 69.2ms\n948:\tlearn: 0.2297789\ttotal: 1.26s\tremaining: 67.9ms\n949:\tlearn: 0.2296886\ttotal: 1.26s\tremaining: 66.5ms\n950:\tlearn: 0.2295969\ttotal: 1.26s\tremaining: 65.2ms\n951:\tlearn: 0.2294750\ttotal: 1.27s\tremaining: 63.9ms\n952:\tlearn: 0.2293852\ttotal: 1.27s\tremaining: 62.5ms\n953:\tlearn: 0.2292566\ttotal: 1.27s\tremaining: 61.2ms\n954:\tlearn: 0.2291288\ttotal: 1.27s\tremaining: 59.9ms\n955:\tlearn: 0.2289669\ttotal: 1.27s\tremaining: 58.5ms\n956:\tlearn: 0.2287992\ttotal: 1.27s\tremaining: 57.2ms\n957:\tlearn: 0.2286856\ttotal: 1.27s\tremaining: 55.9ms\n958:\tlearn: 0.2285741\ttotal: 1.27s\tremaining: 54.5ms\n959:\tlearn: 0.2283999\ttotal: 1.28s\tremaining: 53.2ms\n960:\tlearn: 0.2283209\ttotal: 1.28s\tremaining: 51.9ms\n961:\tlearn: 0.2282311\ttotal: 1.28s\tremaining: 50.6ms\n962:\tlearn: 0.2280699\ttotal: 1.28s\tremaining: 49.2ms\n963:\tlearn: 0.2279441\ttotal: 1.28s\tremaining: 47.9ms\n964:\tlearn: 0.2277671\ttotal: 1.28s\tremaining: 46.6ms\n965:\tlearn: 0.2276439\ttotal: 1.28s\tremaining: 45.2ms\n966:\tlearn: 0.2275516\ttotal: 1.29s\tremaining: 43.9ms\n967:\tlearn: 0.2274655\ttotal: 1.29s\tremaining: 42.6ms\n968:\tlearn: 0.2273657\ttotal: 1.29s\tremaining: 41.3ms\n969:\tlearn: 0.2272552\ttotal: 1.29s\tremaining: 39.9ms\n970:\tlearn: 0.2271202\ttotal: 1.29s\tremaining: 38.6ms\n971:\tlearn: 0.2269476\ttotal: 1.29s\tremaining: 37.3ms\n972:\tlearn: 0.2267795\ttotal: 1.29s\tremaining: 36ms\n973:\tlearn: 0.2266655\ttotal: 1.3s\tremaining: 34.6ms\n974:\tlearn: 0.2265102\ttotal: 1.3s\tremaining: 33.3ms\n975:\tlearn: 0.2263874\ttotal: 1.3s\tremaining: 32ms\n976:\tlearn: 0.2262242\ttotal: 1.3s\tremaining: 30.6ms\n977:\tlearn: 0.2260340\ttotal: 1.3s\tremaining: 29.3ms\n978:\tlearn: 0.2259051\ttotal: 1.3s\tremaining: 28ms\n979:\tlearn: 0.2257953\ttotal: 1.3s\tremaining: 26.6ms\n980:\tlearn: 0.2256369\ttotal: 1.31s\tremaining: 25.3ms\n981:\tlearn: 0.2255181\ttotal: 1.31s\tremaining: 24ms\n982:\tlearn: 0.2253744\ttotal: 1.31s\tremaining: 22.6ms\n983:\tlearn: 0.2253042\ttotal: 1.31s\tremaining: 21.3ms\n984:\tlearn: 0.2251955\ttotal: 1.31s\tremaining: 20ms\n985:\tlearn: 0.2250286\ttotal: 1.31s\tremaining: 18.7ms\n986:\tlearn: 0.2248336\ttotal: 1.31s\tremaining: 17.3ms\n987:\tlearn: 0.2246963\ttotal: 1.32s\tremaining: 16ms\n988:\tlearn: 0.2245518\ttotal: 1.32s\tremaining: 14.7ms\n989:\tlearn: 0.2244328\ttotal: 1.32s\tremaining: 13.3ms\n990:\tlearn: 0.2242437\ttotal: 1.32s\tremaining: 12ms\n991:\tlearn: 0.2241087\ttotal: 1.32s\tremaining: 10.7ms\n992:\tlearn: 0.2239619\ttotal: 1.32s\tremaining: 9.33ms\n993:\tlearn: 0.2238540\ttotal: 1.32s\tremaining: 8ms\n994:\tlearn: 0.2237682\ttotal: 1.33s\tremaining: 6.66ms\n995:\tlearn: 0.2235843\ttotal: 1.33s\tremaining: 5.33ms\n996:\tlearn: 0.2234413\ttotal: 1.33s\tremaining: 4ms\n997:\tlearn: 0.2233262\ttotal: 1.33s\tremaining: 2.67ms\n998:\tlearn: 0.2231933\ttotal: 1.33s\tremaining: 1.33ms\n999:\tlearn: 0.2231028\ttotal: 1.33s\tremaining: 0us\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"name":"stdout","text":" Model Accuracy Precision Recall F1 Score\n0 Random Forest 0.752665 0.686394 0.660551 0.669750\n1 Support Vector Classifier 0.773987 0.721856 0.665816 0.681222\n2 Logistic Regression 0.763326 0.702406 0.663184 0.675493\n3 Decision Tree 0.695096 0.620161 0.620728 0.620441\n4 K-Nearest Neighbors 0.735608 0.661683 0.639267 0.646975\n5 Gradient Boosting 0.773987 0.717072 0.689528 0.699925\n6 AdaBoost 0.782516 0.728192 0.712026 0.718984\n7 CatBoost 0.761194 0.699333 0.683050 0.689800\n8 Extra Trees 0.761194 0.699206 0.659337 0.671569\n9 XGBoost 0.727079 0.656931 0.652337 0.654464\n10 Bagging Classifier 0.733475 0.657757 0.633050 0.641036\n","output_type":"stream"}]},{"cell_type":"code","source":"!pip install mlextend","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:10.786541Z","iopub.execute_input":"2024-07-21T17:50:10.786984Z","iopub.status.idle":"2024-07-21T17:50:12.927221Z","shell.execute_reply.started":"2024-07-21T17:50:10.786944Z","shell.execute_reply":"2024-07-21T17:50:12.925519Z"},"trusted":true},"execution_count":74,"outputs":[{"name":"stdout","text":"\u001b[31mERROR: Could not find a version that satisfies the requirement mlextend (from versions: none)\u001b[0m\u001b[31m\n\u001b[0m\u001b[31mERROR: No matching distribution found for mlextend\u001b[0m\u001b[31m\n\u001b[0m","output_type":"stream"}]},{"cell_type":"code","source":"from mlxtend.classifier import StackingClassifier\n# Define base learners and meta learner for stacking classifier\nbase_learners = [RandomForestClassifier(), SVC(), LogisticRegression(), DecisionTreeClassifier(), \n KNeighborsClassifier(), GradientBoostingClassifier(), AdaBoostClassifier(),\n CatBoostClassifier(), ExtraTreesClassifier(), XGBClassifier(), BaggingClassifier()]\nmeta_learner = LogisticRegression()\n# Initialize Stacking Classifier\nstack = StackingClassifier(classifiers=base_learners, meta_classifier=meta_learner, use_probas=False, average_probas=False)\n# Train Stacking Classifier\nstack.fit(X_train, y_train)\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:12.929336Z","iopub.execute_input":"2024-07-21T17:50:12.929692Z","iopub.status.idle":"2024-07-21T17:50:16.120676Z","shell.execute_reply.started":"2024-07-21T17:50:12.929663Z","shell.execute_reply":"2024-07-21T17:50:16.118946Z"},"trusted":true},"execution_count":75,"outputs":[{"name":"stdout","text":"Learning rate set to 0.013477\n0:\tlearn: 0.6838656\ttotal: 1.71ms\tremaining: 1.71s\n1:\tlearn: 0.6758078\ttotal: 3.06ms\tremaining: 1.52s\n2:\tlearn: 0.6674481\ttotal: 4.36ms\tremaining: 1.45s\n3:\tlearn: 0.6583720\ttotal: 5.62ms\tremaining: 1.4s\n4:\tlearn: 0.6509284\ttotal: 7ms\tremaining: 1.39s\n5:\tlearn: 0.6431915\ttotal: 8.45ms\tremaining: 1.4s\n6:\tlearn: 0.6373617\ttotal: 9.69ms\tremaining: 1.37s\n7:\tlearn: 0.6305452\ttotal: 10.9ms\tremaining: 1.36s\n8:\tlearn: 0.6240415\ttotal: 12.2ms\tremaining: 1.34s\n9:\tlearn: 0.6181451\ttotal: 13.5ms\tremaining: 1.33s\n10:\tlearn: 0.6116032\ttotal: 14.7ms\tremaining: 1.32s\n11:\tlearn: 0.6057016\ttotal: 16ms\tremaining: 1.32s\n12:\tlearn: 0.5992679\ttotal: 17.3ms\tremaining: 1.31s\n13:\tlearn: 0.5938989\ttotal: 18.5ms\tremaining: 1.3s\n14:\tlearn: 0.5881622\ttotal: 19.7ms\tremaining: 1.3s\n15:\tlearn: 0.5824536\ttotal: 21ms\tremaining: 1.29s\n16:\tlearn: 0.5772842\ttotal: 22.3ms\tremaining: 1.29s\n17:\tlearn: 0.5721793\ttotal: 23.5ms\tremaining: 1.28s\n18:\tlearn: 0.5690468\ttotal: 24.6ms\tremaining: 1.27s\n19:\tlearn: 0.5644471\ttotal: 25.9ms\tremaining: 1.27s\n20:\tlearn: 0.5608056\ttotal: 27.1ms\tremaining: 1.26s\n21:\tlearn: 0.5562242\ttotal: 28.4ms\tremaining: 1.26s\n22:\tlearn: 0.5522125\ttotal: 29.7ms\tremaining: 1.26s\n23:\tlearn: 0.5479600\ttotal: 30.9ms\tremaining: 1.26s\n24:\tlearn: 0.5443633\ttotal: 32.2ms\tremaining: 1.25s\n25:\tlearn: 0.5405790\ttotal: 33.4ms\tremaining: 1.25s\n26:\tlearn: 0.5364419\ttotal: 34.9ms\tremaining: 1.26s\n27:\tlearn: 0.5329990\ttotal: 36.2ms\tremaining: 1.25s\n28:\tlearn: 0.5298083\ttotal: 37.4ms\tremaining: 1.25s\n29:\tlearn: 0.5257863\ttotal: 38.7ms\tremaining: 1.25s\n30:\tlearn: 0.5225180\ttotal: 40ms\tremaining: 1.25s\n31:\tlearn: 0.5197893\ttotal: 41.3ms\tremaining: 1.25s\n32:\tlearn: 0.5166048\ttotal: 42.7ms\tremaining: 1.25s\n33:\tlearn: 0.5133304\ttotal: 43.9ms\tremaining: 1.25s\n34:\tlearn: 0.5101360\ttotal: 45.2ms\tremaining: 1.25s\n35:\tlearn: 0.5067611\ttotal: 46.6ms\tremaining: 1.25s\n36:\tlearn: 0.5038938\ttotal: 47.9ms\tremaining: 1.25s\n37:\tlearn: 0.5012076\ttotal: 49.3ms\tremaining: 1.25s\n38:\tlearn: 0.4986865\ttotal: 50.8ms\tremaining: 1.25s\n39:\tlearn: 0.4960242\ttotal: 52.1ms\tremaining: 1.25s\n40:\tlearn: 0.4941094\ttotal: 53.4ms\tremaining: 1.25s\n41:\tlearn: 0.4917178\ttotal: 54.9ms\tremaining: 1.25s\n42:\tlearn: 0.4894410\ttotal: 56.3ms\tremaining: 1.25s\n43:\tlearn: 0.4876576\ttotal: 57.7ms\tremaining: 1.25s\n44:\tlearn: 0.4861331\ttotal: 59ms\tremaining: 1.25s\n45:\tlearn: 0.4833094\ttotal: 60.3ms\tremaining: 1.25s\n46:\tlearn: 0.4809459\ttotal: 61.6ms\tremaining: 1.25s\n47:\tlearn: 0.4789782\ttotal: 62.9ms\tremaining: 1.25s\n48:\tlearn: 0.4774782\ttotal: 64.2ms\tremaining: 1.25s\n49:\tlearn: 0.4753783\ttotal: 65.5ms\tremaining: 1.24s\n50:\tlearn: 0.4728362\ttotal: 66.8ms\tremaining: 1.24s\n51:\tlearn: 0.4706000\ttotal: 68.1ms\tremaining: 1.24s\n52:\tlearn: 0.4685507\ttotal: 69.7ms\tremaining: 1.25s\n53:\tlearn: 0.4666814\ttotal: 71.1ms\tremaining: 1.24s\n54:\tlearn: 0.4648348\ttotal: 72.4ms\tremaining: 1.24s\n55:\tlearn: 0.4628744\ttotal: 73.8ms\tremaining: 1.24s\n56:\tlearn: 0.4612058\ttotal: 75.4ms\tremaining: 1.25s\n57:\tlearn: 0.4591243\ttotal: 76.8ms\tremaining: 1.25s\n58:\tlearn: 0.4571499\ttotal: 78.3ms\tremaining: 1.25s\n59:\tlearn: 0.4556636\ttotal: 79.8ms\tremaining: 1.25s\n60:\tlearn: 0.4540737\ttotal: 81.4ms\tremaining: 1.25s\n61:\tlearn: 0.4524821\ttotal: 82.7ms\tremaining: 1.25s\n62:\tlearn: 0.4511638\ttotal: 84.1ms\tremaining: 1.25s\n63:\tlearn: 0.4496792\ttotal: 85.5ms\tremaining: 1.25s\n64:\tlearn: 0.4482901\ttotal: 86.9ms\tremaining: 1.25s\n65:\tlearn: 0.4468370\ttotal: 88.2ms\tremaining: 1.25s\n66:\tlearn: 0.4452703\ttotal: 89.6ms\tremaining: 1.25s\n67:\tlearn: 0.4441687\ttotal: 91ms\tremaining: 1.25s\n68:\tlearn: 0.4427134\ttotal: 92.3ms\tremaining: 1.25s\n69:\tlearn: 0.4411629\ttotal: 93.7ms\tremaining: 1.24s\n70:\tlearn: 0.4398318\ttotal: 95ms\tremaining: 1.24s\n71:\tlearn: 0.4385469\ttotal: 96.4ms\tremaining: 1.24s\n72:\tlearn: 0.4373829\ttotal: 97.7ms\tremaining: 1.24s\n73:\tlearn: 0.4360992\ttotal: 99.2ms\tremaining: 1.24s\n74:\tlearn: 0.4350130\ttotal: 101ms\tremaining: 1.24s\n75:\tlearn: 0.4340907\ttotal: 102ms\tremaining: 1.24s\n76:\tlearn: 0.4330526\ttotal: 103ms\tremaining: 1.24s\n77:\tlearn: 0.4321139\ttotal: 104ms\tremaining: 1.23s\n78:\tlearn: 0.4307044\ttotal: 106ms\tremaining: 1.23s\n79:\tlearn: 0.4299842\ttotal: 107ms\tremaining: 1.23s\n80:\tlearn: 0.4291736\ttotal: 108ms\tremaining: 1.23s\n81:\tlearn: 0.4280273\ttotal: 110ms\tremaining: 1.23s\n82:\tlearn: 0.4269721\ttotal: 111ms\tremaining: 1.23s\n83:\tlearn: 0.4259817\ttotal: 112ms\tremaining: 1.23s\n84:\tlearn: 0.4250015\ttotal: 114ms\tremaining: 1.22s\n85:\tlearn: 0.4239173\ttotal: 115ms\tremaining: 1.23s\n86:\tlearn: 0.4229586\ttotal: 117ms\tremaining: 1.23s\n87:\tlearn: 0.4220666\ttotal: 119ms\tremaining: 1.23s\n88:\tlearn: 0.4210140\ttotal: 120ms\tremaining: 1.23s\n89:\tlearn: 0.4200321\ttotal: 121ms\tremaining: 1.23s\n90:\tlearn: 0.4190811\ttotal: 123ms\tremaining: 1.22s\n91:\tlearn: 0.4178803\ttotal: 124ms\tremaining: 1.22s\n92:\tlearn: 0.4171507\ttotal: 125ms\tremaining: 1.22s\n93:\tlearn: 0.4162712\ttotal: 127ms\tremaining: 1.22s\n94:\tlearn: 0.4150368\ttotal: 128ms\tremaining: 1.22s\n95:\tlearn: 0.4140393\ttotal: 129ms\tremaining: 1.22s\n96:\tlearn: 0.4131950\ttotal: 130ms\tremaining: 1.21s\n97:\tlearn: 0.4120038\ttotal: 132ms\tremaining: 1.21s\n98:\tlearn: 0.4112120\ttotal: 133ms\tremaining: 1.21s\n99:\tlearn: 0.4107803\ttotal: 134ms\tremaining: 1.21s\n100:\tlearn: 0.4099592\ttotal: 135ms\tremaining: 1.21s\n101:\tlearn: 0.4094548\ttotal: 137ms\tremaining: 1.2s\n102:\tlearn: 0.4086998\ttotal: 138ms\tremaining: 1.2s\n103:\tlearn: 0.4080693\ttotal: 139ms\tremaining: 1.2s\n104:\tlearn: 0.4072141\ttotal: 141ms\tremaining: 1.2s\n105:\tlearn: 0.4068332\ttotal: 142ms\tremaining: 1.2s\n106:\tlearn: 0.4061805\ttotal: 143ms\tremaining: 1.19s\n107:\tlearn: 0.4057864\ttotal: 144ms\tremaining: 1.19s\n108:\tlearn: 0.4050086\ttotal: 146ms\tremaining: 1.19s\n109:\tlearn: 0.4043780\ttotal: 147ms\tremaining: 1.19s\n110:\tlearn: 0.4035184\ttotal: 148ms\tremaining: 1.19s\n111:\tlearn: 0.4029431\ttotal: 150ms\tremaining: 1.19s\n112:\tlearn: 0.4023117\ttotal: 151ms\tremaining: 1.18s\n113:\tlearn: 0.4017164\ttotal: 153ms\tremaining: 1.19s\n114:\tlearn: 0.4010964\ttotal: 154ms\tremaining: 1.19s\n115:\tlearn: 0.4002701\ttotal: 155ms\tremaining: 1.18s\n116:\tlearn: 0.3995851\ttotal: 157ms\tremaining: 1.18s\n117:\tlearn: 0.3988357\ttotal: 158ms\tremaining: 1.18s\n118:\tlearn: 0.3981552\ttotal: 160ms\tremaining: 1.18s\n119:\tlearn: 0.3975807\ttotal: 161ms\tremaining: 1.18s\n120:\tlearn: 0.3969913\ttotal: 162ms\tremaining: 1.18s\n121:\tlearn: 0.3963573\ttotal: 164ms\tremaining: 1.18s\n122:\tlearn: 0.3957974\ttotal: 165ms\tremaining: 1.18s\n123:\tlearn: 0.3952270\ttotal: 166ms\tremaining: 1.18s\n124:\tlearn: 0.3946346\ttotal: 168ms\tremaining: 1.17s\n125:\tlearn: 0.3941434\ttotal: 169ms\tremaining: 1.17s\n126:\tlearn: 0.3935366\ttotal: 170ms\tremaining: 1.17s\n127:\tlearn: 0.3928694\ttotal: 172ms\tremaining: 1.17s\n128:\tlearn: 0.3923522\ttotal: 173ms\tremaining: 1.17s\n129:\tlearn: 0.3917551\ttotal: 174ms\tremaining: 1.17s\n130:\tlearn: 0.3912321\ttotal: 176ms\tremaining: 1.17s\n131:\tlearn: 0.3907711\ttotal: 177ms\tremaining: 1.16s\n132:\tlearn: 0.3903551\ttotal: 178ms\tremaining: 1.16s\n133:\tlearn: 0.3895483\ttotal: 180ms\tremaining: 1.16s\n134:\tlearn: 0.3891096\ttotal: 181ms\tremaining: 1.16s\n135:\tlearn: 0.3886794\ttotal: 182ms\tremaining: 1.16s\n136:\tlearn: 0.3881677\ttotal: 184ms\tremaining: 1.16s\n137:\tlearn: 0.3875279\ttotal: 186ms\tremaining: 1.16s\n138:\tlearn: 0.3870149\ttotal: 188ms\tremaining: 1.16s\n139:\tlearn: 0.3864852\ttotal: 189ms\tremaining: 1.16s\n140:\tlearn: 0.3860731\ttotal: 191ms\tremaining: 1.16s\n141:\tlearn: 0.3855636\ttotal: 192ms\tremaining: 1.16s\n142:\tlearn: 0.3851173\ttotal: 194ms\tremaining: 1.16s\n143:\tlearn: 0.3847052\ttotal: 195ms\tremaining: 1.16s\n144:\tlearn: 0.3839497\ttotal: 196ms\tremaining: 1.16s\n145:\tlearn: 0.3834139\ttotal: 198ms\tremaining: 1.16s\n146:\tlearn: 0.3829551\ttotal: 199ms\tremaining: 1.16s\n147:\tlearn: 0.3825137\ttotal: 200ms\tremaining: 1.15s\n148:\tlearn: 0.3820628\ttotal: 202ms\tremaining: 1.15s\n149:\tlearn: 0.3816702\ttotal: 203ms\tremaining: 1.15s\n150:\tlearn: 0.3812220\ttotal: 205ms\tremaining: 1.15s\n151:\tlearn: 0.3807033\ttotal: 206ms\tremaining: 1.15s\n152:\tlearn: 0.3802626\ttotal: 208ms\tremaining: 1.15s\n153:\tlearn: 0.3798004\ttotal: 209ms\tremaining: 1.15s\n154:\tlearn: 0.3796631\ttotal: 210ms\tremaining: 1.15s\n155:\tlearn: 0.3794263\ttotal: 212ms\tremaining: 1.14s\n156:\tlearn: 0.3790312\ttotal: 213ms\tremaining: 1.15s\n157:\tlearn: 0.3785859\ttotal: 215ms\tremaining: 1.14s\n158:\tlearn: 0.3782018\ttotal: 216ms\tremaining: 1.14s\n159:\tlearn: 0.3776881\ttotal: 217ms\tremaining: 1.14s\n160:\tlearn: 0.3772753\ttotal: 219ms\tremaining: 1.14s\n161:\tlearn: 0.3767445\ttotal: 220ms\tremaining: 1.14s\n162:\tlearn: 0.3762077\ttotal: 221ms\tremaining: 1.14s\n163:\tlearn: 0.3757532\ttotal: 223ms\tremaining: 1.13s\n164:\tlearn: 0.3754873\ttotal: 224ms\tremaining: 1.13s\n165:\tlearn: 0.3750546\ttotal: 225ms\tremaining: 1.13s\n166:\tlearn: 0.3746284\ttotal: 226ms\tremaining: 1.13s\n167:\tlearn: 0.3742116\ttotal: 228ms\tremaining: 1.13s\n168:\tlearn: 0.3738200\ttotal: 229ms\tremaining: 1.13s\n169:\tlearn: 0.3734268\ttotal: 231ms\tremaining: 1.13s\n170:\tlearn: 0.3731184\ttotal: 232ms\tremaining: 1.13s\n171:\tlearn: 0.3727546\ttotal: 233ms\tremaining: 1.12s\n172:\tlearn: 0.3723824\ttotal: 235ms\tremaining: 1.12s\n173:\tlearn: 0.3720684\ttotal: 236ms\tremaining: 1.12s\n174:\tlearn: 0.3716427\ttotal: 238ms\tremaining: 1.12s\n175:\tlearn: 0.3711650\ttotal: 240ms\tremaining: 1.12s\n176:\tlearn: 0.3707969\ttotal: 242ms\tremaining: 1.12s\n177:\tlearn: 0.3704168\ttotal: 244ms\tremaining: 1.13s\n178:\tlearn: 0.3699671\ttotal: 245ms\tremaining: 1.13s\n179:\tlearn: 0.3695791\ttotal: 247ms\tremaining: 1.12s\n180:\tlearn: 0.3691587\ttotal: 250ms\tremaining: 1.13s\n181:\tlearn: 0.3688321\ttotal: 253ms\tremaining: 1.14s\n182:\tlearn: 0.3684468\ttotal: 256ms\tremaining: 1.14s\n183:\tlearn: 0.3681522\ttotal: 260ms\tremaining: 1.15s\n184:\tlearn: 0.3679301\ttotal: 262ms\tremaining: 1.15s\n185:\tlearn: 0.3676040\ttotal: 263ms\tremaining: 1.15s\n186:\tlearn: 0.3672947\ttotal: 264ms\tremaining: 1.15s\n187:\tlearn: 0.3668426\ttotal: 266ms\tremaining: 1.15s\n188:\tlearn: 0.3664749\ttotal: 267ms\tremaining: 1.15s\n189:\tlearn: 0.3659812\ttotal: 269ms\tremaining: 1.15s\n190:\tlearn: 0.3656888\ttotal: 270ms\tremaining: 1.14s\n191:\tlearn: 0.3653473\ttotal: 271ms\tremaining: 1.14s\n192:\tlearn: 0.3649575\ttotal: 273ms\tremaining: 1.14s\n193:\tlearn: 0.3645062\ttotal: 275ms\tremaining: 1.14s\n194:\tlearn: 0.3641390\ttotal: 277ms\tremaining: 1.14s\n195:\tlearn: 0.3638571\ttotal: 279ms\tremaining: 1.14s\n196:\tlearn: 0.3635655\ttotal: 280ms\tremaining: 1.14s\n197:\tlearn: 0.3631415\ttotal: 282ms\tremaining: 1.14s\n198:\tlearn: 0.3628179\ttotal: 283ms\tremaining: 1.14s\n199:\tlearn: 0.3625360\ttotal: 285ms\tremaining: 1.14s\n200:\tlearn: 0.3623035\ttotal: 286ms\tremaining: 1.14s\n201:\tlearn: 0.3619772\ttotal: 287ms\tremaining: 1.14s\n202:\tlearn: 0.3616644\ttotal: 289ms\tremaining: 1.13s\n203:\tlearn: 0.3615650\ttotal: 290ms\tremaining: 1.13s\n204:\tlearn: 0.3612219\ttotal: 292ms\tremaining: 1.13s\n205:\tlearn: 0.3607920\ttotal: 293ms\tremaining: 1.13s\n206:\tlearn: 0.3604719\ttotal: 295ms\tremaining: 1.13s\n207:\tlearn: 0.3602678\ttotal: 296ms\tremaining: 1.13s\n208:\tlearn: 0.3600256\ttotal: 297ms\tremaining: 1.13s\n209:\tlearn: 0.3597211\ttotal: 299ms\tremaining: 1.12s\n210:\tlearn: 0.3593575\ttotal: 300ms\tremaining: 1.12s\n211:\tlearn: 0.3590378\ttotal: 302ms\tremaining: 1.12s\n212:\tlearn: 0.3589888\ttotal: 303ms\tremaining: 1.12s\n213:\tlearn: 0.3586668\ttotal: 304ms\tremaining: 1.12s\n214:\tlearn: 0.3586154\ttotal: 305ms\tremaining: 1.11s\n215:\tlearn: 0.3583470\ttotal: 307ms\tremaining: 1.11s\n216:\tlearn: 0.3581083\ttotal: 308ms\tremaining: 1.11s\n217:\tlearn: 0.3578125\ttotal: 309ms\tremaining: 1.11s\n218:\tlearn: 0.3574743\ttotal: 311ms\tremaining: 1.11s\n219:\tlearn: 0.3571345\ttotal: 312ms\tremaining: 1.11s\n220:\tlearn: 0.3568790\ttotal: 314ms\tremaining: 1.1s\n221:\tlearn: 0.3564717\ttotal: 315ms\tremaining: 1.1s\n222:\tlearn: 0.3560492\ttotal: 316ms\tremaining: 1.1s\n223:\tlearn: 0.3557979\ttotal: 320ms\tremaining: 1.11s\n224:\tlearn: 0.3555973\ttotal: 321ms\tremaining: 1.11s\n225:\tlearn: 0.3552493\ttotal: 323ms\tremaining: 1.1s\n226:\tlearn: 0.3550137\ttotal: 324ms\tremaining: 1.1s\n227:\tlearn: 0.3546823\ttotal: 325ms\tremaining: 1.1s\n228:\tlearn: 0.3543253\ttotal: 327ms\tremaining: 1.1s\n229:\tlearn: 0.3541066\ttotal: 328ms\tremaining: 1.1s\n230:\tlearn: 0.3538600\ttotal: 330ms\tremaining: 1.1s\n231:\tlearn: 0.3534868\ttotal: 331ms\tremaining: 1.09s\n232:\tlearn: 0.3531985\ttotal: 332ms\tremaining: 1.09s\n233:\tlearn: 0.3529198\ttotal: 333ms\tremaining: 1.09s\n234:\tlearn: 0.3526271\ttotal: 335ms\tremaining: 1.09s\n235:\tlearn: 0.3523048\ttotal: 336ms\tremaining: 1.09s\n236:\tlearn: 0.3520437\ttotal: 337ms\tremaining: 1.08s\n237:\tlearn: 0.3516882\ttotal: 338ms\tremaining: 1.08s\n238:\tlearn: 0.3514538\ttotal: 340ms\tremaining: 1.08s\n239:\tlearn: 0.3512176\ttotal: 341ms\tremaining: 1.08s\n240:\tlearn: 0.3509431\ttotal: 342ms\tremaining: 1.08s\n241:\tlearn: 0.3506362\ttotal: 343ms\tremaining: 1.07s\n242:\tlearn: 0.3503934\ttotal: 345ms\tremaining: 1.07s\n243:\tlearn: 0.3501993\ttotal: 346ms\tremaining: 1.07s\n244:\tlearn: 0.3500023\ttotal: 347ms\tremaining: 1.07s\n245:\tlearn: 0.3498073\ttotal: 348ms\tremaining: 1.07s\n246:\tlearn: 0.3496334\ttotal: 349ms\tremaining: 1.06s\n247:\tlearn: 0.3493233\ttotal: 351ms\tremaining: 1.06s\n248:\tlearn: 0.3490207\ttotal: 352ms\tremaining: 1.06s\n249:\tlearn: 0.3487930\ttotal: 353ms\tremaining: 1.06s\n250:\tlearn: 0.3485273\ttotal: 355ms\tremaining: 1.06s\n251:\tlearn: 0.3483183\ttotal: 356ms\tremaining: 1.05s\n252:\tlearn: 0.3481449\ttotal: 357ms\tremaining: 1.05s\n253:\tlearn: 0.3479113\ttotal: 358ms\tremaining: 1.05s\n254:\tlearn: 0.3476127\ttotal: 360ms\tremaining: 1.05s\n255:\tlearn: 0.3472854\ttotal: 361ms\tremaining: 1.05s\n256:\tlearn: 0.3469425\ttotal: 362ms\tremaining: 1.05s\n257:\tlearn: 0.3468701\ttotal: 363ms\tremaining: 1.04s\n258:\tlearn: 0.3466920\ttotal: 365ms\tremaining: 1.04s\n259:\tlearn: 0.3464607\ttotal: 366ms\tremaining: 1.04s\n260:\tlearn: 0.3462171\ttotal: 367ms\tremaining: 1.04s\n261:\tlearn: 0.3461673\ttotal: 368ms\tremaining: 1.04s\n262:\tlearn: 0.3459325\ttotal: 370ms\tremaining: 1.03s\n263:\tlearn: 0.3456664\ttotal: 371ms\tremaining: 1.03s\n264:\tlearn: 0.3453805\ttotal: 372ms\tremaining: 1.03s\n265:\tlearn: 0.3451982\ttotal: 374ms\tremaining: 1.03s\n266:\tlearn: 0.3449740\ttotal: 375ms\tremaining: 1.03s\n267:\tlearn: 0.3447986\ttotal: 377ms\tremaining: 1.03s\n268:\tlearn: 0.3445476\ttotal: 378ms\tremaining: 1.03s\n269:\tlearn: 0.3443443\ttotal: 379ms\tremaining: 1.02s\n270:\tlearn: 0.3440121\ttotal: 381ms\tremaining: 1.02s\n271:\tlearn: 0.3437523\ttotal: 382ms\tremaining: 1.02s\n272:\tlearn: 0.3434180\ttotal: 383ms\tremaining: 1.02s\n273:\tlearn: 0.3431703\ttotal: 385ms\tremaining: 1.02s\n274:\tlearn: 0.3429551\ttotal: 386ms\tremaining: 1.02s\n275:\tlearn: 0.3426571\ttotal: 387ms\tremaining: 1.02s\n276:\tlearn: 0.3424543\ttotal: 389ms\tremaining: 1.01s\n277:\tlearn: 0.3421855\ttotal: 390ms\tremaining: 1.01s\n278:\tlearn: 0.3419199\ttotal: 391ms\tremaining: 1.01s\n279:\tlearn: 0.3416234\ttotal: 392ms\tremaining: 1.01s\n280:\tlearn: 0.3414410\ttotal: 394ms\tremaining: 1.01s\n281:\tlearn: 0.3410844\ttotal: 395ms\tremaining: 1.01s\n282:\tlearn: 0.3407167\ttotal: 397ms\tremaining: 1s\n283:\tlearn: 0.3406982\ttotal: 398ms\tremaining: 1s\n284:\tlearn: 0.3404485\ttotal: 399ms\tremaining: 1s\n285:\tlearn: 0.3402440\ttotal: 400ms\tremaining: 999ms\n286:\tlearn: 0.3399089\ttotal: 401ms\tremaining: 997ms\n287:\tlearn: 0.3397277\ttotal: 403ms\tremaining: 996ms\n288:\tlearn: 0.3394403\ttotal: 404ms\tremaining: 994ms\n289:\tlearn: 0.3392802\ttotal: 406ms\tremaining: 993ms\n290:\tlearn: 0.3389966\ttotal: 407ms\tremaining: 992ms\n291:\tlearn: 0.3387269\ttotal: 408ms\tremaining: 990ms\n292:\tlearn: 0.3384379\ttotal: 410ms\tremaining: 988ms\n293:\tlearn: 0.3382130\ttotal: 411ms\tremaining: 987ms\n294:\tlearn: 0.3380097\ttotal: 412ms\tremaining: 985ms\n295:\tlearn: 0.3376649\ttotal: 414ms\tremaining: 984ms\n296:\tlearn: 0.3373943\ttotal: 415ms\tremaining: 982ms\n297:\tlearn: 0.3373692\ttotal: 416ms\tremaining: 980ms\n298:\tlearn: 0.3372242\ttotal: 417ms\tremaining: 979ms\n299:\tlearn: 0.3371052\ttotal: 419ms\tremaining: 978ms\n300:\tlearn: 0.3368458\ttotal: 420ms\tremaining: 976ms\n301:\tlearn: 0.3365440\ttotal: 422ms\tremaining: 974ms\n302:\tlearn: 0.3364032\ttotal: 423ms\tremaining: 973ms\n303:\tlearn: 0.3361169\ttotal: 424ms\tremaining: 972ms\n304:\tlearn: 0.3358718\ttotal: 426ms\tremaining: 970ms\n305:\tlearn: 0.3356318\ttotal: 427ms\tremaining: 969ms\n306:\tlearn: 0.3356035\ttotal: 428ms\tremaining: 967ms\n307:\tlearn: 0.3354056\ttotal: 429ms\tremaining: 965ms\n308:\tlearn: 0.3350256\ttotal: 431ms\tremaining: 963ms\n309:\tlearn: 0.3348244\ttotal: 432ms\tremaining: 962ms\n310:\tlearn: 0.3344690\ttotal: 433ms\tremaining: 960ms\n311:\tlearn: 0.3341631\ttotal: 435ms\tremaining: 959ms\n312:\tlearn: 0.3341294\ttotal: 436ms\tremaining: 956ms\n313:\tlearn: 0.3339216\ttotal: 437ms\tremaining: 955ms\n314:\tlearn: 0.3337193\ttotal: 438ms\tremaining: 953ms\n315:\tlearn: 0.3335134\ttotal: 440ms\tremaining: 952ms\n316:\tlearn: 0.3332284\ttotal: 441ms\tremaining: 951ms\n317:\tlearn: 0.3330645\ttotal: 443ms\tremaining: 949ms\n318:\tlearn: 0.3328726\ttotal: 444ms\tremaining: 948ms\n319:\tlearn: 0.3326566\ttotal: 445ms\tremaining: 946ms\n320:\tlearn: 0.3324417\ttotal: 447ms\tremaining: 945ms\n321:\tlearn: 0.3322102\ttotal: 448ms\tremaining: 943ms\n322:\tlearn: 0.3319472\ttotal: 449ms\tremaining: 942ms\n323:\tlearn: 0.3318250\ttotal: 450ms\tremaining: 940ms\n324:\tlearn: 0.3315776\ttotal: 452ms\tremaining: 938ms\n325:\tlearn: 0.3314118\ttotal: 453ms\tremaining: 937ms\n326:\tlearn: 0.3312500\ttotal: 454ms\tremaining: 935ms\n327:\tlearn: 0.3310297\ttotal: 456ms\tremaining: 933ms\n328:\tlearn: 0.3308546\ttotal: 457ms\tremaining: 932ms\n329:\tlearn: 0.3306564\ttotal: 458ms\tremaining: 930ms\n330:\tlearn: 0.3305563\ttotal: 459ms\tremaining: 928ms\n331:\tlearn: 0.3304758\ttotal: 461ms\tremaining: 927ms\n332:\tlearn: 0.3301638\ttotal: 462ms\tremaining: 925ms\n333:\tlearn: 0.3298371\ttotal: 463ms\tremaining: 924ms\n334:\tlearn: 0.3296341\ttotal: 465ms\tremaining: 923ms\n335:\tlearn: 0.3293369\ttotal: 466ms\tremaining: 921ms\n336:\tlearn: 0.3291061\ttotal: 467ms\tremaining: 920ms\n337:\tlearn: 0.3288663\ttotal: 469ms\tremaining: 918ms\n338:\tlearn: 0.3286668\ttotal: 470ms\tremaining: 917ms\n339:\tlearn: 0.3283135\ttotal: 471ms\tremaining: 915ms\n340:\tlearn: 0.3281119\ttotal: 473ms\tremaining: 913ms\n341:\tlearn: 0.3278855\ttotal: 474ms\tremaining: 912ms\n342:\tlearn: 0.3276559\ttotal: 475ms\tremaining: 910ms\n343:\tlearn: 0.3274257\ttotal: 476ms\tremaining: 909ms\n344:\tlearn: 0.3272050\ttotal: 478ms\tremaining: 907ms\n345:\tlearn: 0.3270119\ttotal: 479ms\tremaining: 905ms\n346:\tlearn: 0.3267618\ttotal: 480ms\tremaining: 904ms\n347:\tlearn: 0.3265265\ttotal: 482ms\tremaining: 902ms\n348:\tlearn: 0.3263297\ttotal: 483ms\tremaining: 901ms\n349:\tlearn: 0.3261416\ttotal: 484ms\tremaining: 899ms\n350:\tlearn: 0.3258940\ttotal: 485ms\tremaining: 897ms\n351:\tlearn: 0.3257441\ttotal: 487ms\tremaining: 896ms\n352:\tlearn: 0.3257247\ttotal: 488ms\tremaining: 894ms\n353:\tlearn: 0.3255059\ttotal: 489ms\tremaining: 892ms\n354:\tlearn: 0.3253445\ttotal: 490ms\tremaining: 891ms\n355:\tlearn: 0.3250101\ttotal: 491ms\tremaining: 889ms\n356:\tlearn: 0.3248142\ttotal: 493ms\tremaining: 887ms\n357:\tlearn: 0.3246638\ttotal: 494ms\tremaining: 886ms\n358:\tlearn: 0.3245202\ttotal: 495ms\tremaining: 884ms\n359:\tlearn: 0.3242119\ttotal: 497ms\tremaining: 883ms\n360:\tlearn: 0.3239574\ttotal: 498ms\tremaining: 881ms\n361:\tlearn: 0.3237838\ttotal: 499ms\tremaining: 880ms\n362:\tlearn: 0.3235004\ttotal: 500ms\tremaining: 878ms\n363:\tlearn: 0.3232922\ttotal: 502ms\tremaining: 876ms\n364:\tlearn: 0.3230232\ttotal: 503ms\tremaining: 875ms\n365:\tlearn: 0.3228873\ttotal: 504ms\tremaining: 873ms\n366:\tlearn: 0.3227095\ttotal: 505ms\tremaining: 872ms\n367:\tlearn: 0.3225151\ttotal: 507ms\tremaining: 870ms\n368:\tlearn: 0.3223609\ttotal: 508ms\tremaining: 869ms\n369:\tlearn: 0.3221793\ttotal: 509ms\tremaining: 867ms\n370:\tlearn: 0.3219470\ttotal: 510ms\tremaining: 865ms\n371:\tlearn: 0.3217563\ttotal: 512ms\tremaining: 864ms\n372:\tlearn: 0.3215259\ttotal: 513ms\tremaining: 862ms\n373:\tlearn: 0.3213921\ttotal: 514ms\tremaining: 861ms\n374:\tlearn: 0.3212560\ttotal: 516ms\tremaining: 859ms\n375:\tlearn: 0.3209756\ttotal: 517ms\tremaining: 858ms\n376:\tlearn: 0.3208119\ttotal: 518ms\tremaining: 856ms\n377:\tlearn: 0.3205885\ttotal: 520ms\tremaining: 855ms\n378:\tlearn: 0.3205233\ttotal: 521ms\tremaining: 853ms\n379:\tlearn: 0.3203816\ttotal: 522ms\tremaining: 852ms\n380:\tlearn: 0.3202002\ttotal: 523ms\tremaining: 850ms\n381:\tlearn: 0.3200266\ttotal: 525ms\tremaining: 849ms\n382:\tlearn: 0.3198362\ttotal: 526ms\tremaining: 847ms\n383:\tlearn: 0.3195630\ttotal: 527ms\tremaining: 846ms\n384:\tlearn: 0.3194004\ttotal: 528ms\tremaining: 844ms\n385:\tlearn: 0.3192132\ttotal: 530ms\tremaining: 843ms\n386:\tlearn: 0.3190499\ttotal: 531ms\tremaining: 841ms\n387:\tlearn: 0.3188472\ttotal: 533ms\tremaining: 840ms\n388:\tlearn: 0.3186495\ttotal: 534ms\tremaining: 839ms\n389:\tlearn: 0.3184074\ttotal: 536ms\tremaining: 838ms\n390:\tlearn: 0.3181990\ttotal: 537ms\tremaining: 836ms\n391:\tlearn: 0.3180053\ttotal: 538ms\tremaining: 835ms\n392:\tlearn: 0.3176707\ttotal: 540ms\tremaining: 834ms\n393:\tlearn: 0.3175041\ttotal: 541ms\tremaining: 833ms\n394:\tlearn: 0.3173406\ttotal: 543ms\tremaining: 831ms\n395:\tlearn: 0.3172226\ttotal: 544ms\tremaining: 830ms\n396:\tlearn: 0.3170523\ttotal: 545ms\tremaining: 828ms\n397:\tlearn: 0.3168946\ttotal: 547ms\tremaining: 827ms\n398:\tlearn: 0.3166836\ttotal: 548ms\tremaining: 825ms\n399:\tlearn: 0.3165552\ttotal: 549ms\tremaining: 824ms\n400:\tlearn: 0.3163364\ttotal: 551ms\tremaining: 822ms\n401:\tlearn: 0.3162982\ttotal: 552ms\tremaining: 821ms\n402:\tlearn: 0.3160446\ttotal: 553ms\tremaining: 819ms\n403:\tlearn: 0.3157943\ttotal: 554ms\tremaining: 818ms\n404:\tlearn: 0.3157422\ttotal: 555ms\tremaining: 816ms\n405:\tlearn: 0.3155487\ttotal: 557ms\tremaining: 815ms\n406:\tlearn: 0.3153704\ttotal: 558ms\tremaining: 813ms\n407:\tlearn: 0.3151216\ttotal: 560ms\tremaining: 813ms\n408:\tlearn: 0.3149820\ttotal: 562ms\tremaining: 812ms\n409:\tlearn: 0.3147236\ttotal: 563ms\tremaining: 811ms\n410:\tlearn: 0.3145455\ttotal: 565ms\tremaining: 809ms\n411:\tlearn: 0.3144075\ttotal: 566ms\tremaining: 808ms\n412:\tlearn: 0.3143930\ttotal: 567ms\tremaining: 806ms\n413:\tlearn: 0.3142231\ttotal: 569ms\tremaining: 805ms\n414:\tlearn: 0.3139974\ttotal: 570ms\tremaining: 803ms\n415:\tlearn: 0.3138447\ttotal: 571ms\tremaining: 802ms\n416:\tlearn: 0.3136665\ttotal: 573ms\tremaining: 801ms\n417:\tlearn: 0.3134969\ttotal: 574ms\tremaining: 799ms\n418:\tlearn: 0.3132821\ttotal: 575ms\tremaining: 798ms\n419:\tlearn: 0.3131396\ttotal: 577ms\tremaining: 796ms\n420:\tlearn: 0.3129509\ttotal: 578ms\tremaining: 795ms\n421:\tlearn: 0.3128049\ttotal: 579ms\tremaining: 793ms\n422:\tlearn: 0.3126810\ttotal: 580ms\tremaining: 792ms\n423:\tlearn: 0.3125379\ttotal: 582ms\tremaining: 790ms\n424:\tlearn: 0.3124673\ttotal: 583ms\tremaining: 789ms\n425:\tlearn: 0.3123075\ttotal: 584ms\tremaining: 787ms\n426:\tlearn: 0.3121999\ttotal: 585ms\tremaining: 786ms\n427:\tlearn: 0.3120471\ttotal: 587ms\tremaining: 784ms\n428:\tlearn: 0.3118661\ttotal: 588ms\tremaining: 783ms\n429:\tlearn: 0.3116159\ttotal: 589ms\tremaining: 781ms\n430:\tlearn: 0.3114321\ttotal: 591ms\tremaining: 780ms\n431:\tlearn: 0.3112992\ttotal: 592ms\tremaining: 778ms\n432:\tlearn: 0.3111575\ttotal: 593ms\tremaining: 777ms\n433:\tlearn: 0.3109582\ttotal: 595ms\tremaining: 776ms\n434:\tlearn: 0.3107156\ttotal: 596ms\tremaining: 774ms\n435:\tlearn: 0.3104343\ttotal: 598ms\tremaining: 773ms\n436:\tlearn: 0.3102203\ttotal: 599ms\tremaining: 772ms\n437:\tlearn: 0.3100993\ttotal: 600ms\tremaining: 770ms\n438:\tlearn: 0.3100899\ttotal: 601ms\tremaining: 768ms\n439:\tlearn: 0.3098086\ttotal: 603ms\tremaining: 767ms\n440:\tlearn: 0.3095925\ttotal: 604ms\tremaining: 765ms\n441:\tlearn: 0.3093341\ttotal: 605ms\tremaining: 764ms\n442:\tlearn: 0.3091640\ttotal: 606ms\tremaining: 762ms\n443:\tlearn: 0.3089960\ttotal: 608ms\tremaining: 761ms\n444:\tlearn: 0.3089066\ttotal: 609ms\tremaining: 759ms\n445:\tlearn: 0.3087554\ttotal: 610ms\tremaining: 758ms\n446:\tlearn: 0.3086161\ttotal: 612ms\tremaining: 757ms\n447:\tlearn: 0.3083538\ttotal: 613ms\tremaining: 755ms\n448:\tlearn: 0.3082217\ttotal: 614ms\tremaining: 754ms\n449:\tlearn: 0.3080326\ttotal: 615ms\tremaining: 752ms\n450:\tlearn: 0.3080118\ttotal: 616ms\tremaining: 750ms\n451:\tlearn: 0.3077435\ttotal: 618ms\tremaining: 749ms\n452:\tlearn: 0.3075747\ttotal: 619ms\tremaining: 747ms\n453:\tlearn: 0.3073330\ttotal: 620ms\tremaining: 746ms\n454:\tlearn: 0.3071039\ttotal: 622ms\tremaining: 745ms\n455:\tlearn: 0.3069636\ttotal: 623ms\tremaining: 743ms\n456:\tlearn: 0.3067937\ttotal: 624ms\tremaining: 742ms\n457:\tlearn: 0.3066205\ttotal: 626ms\tremaining: 741ms\n458:\tlearn: 0.3064745\ttotal: 628ms\tremaining: 740ms\n459:\tlearn: 0.3061776\ttotal: 629ms\tremaining: 739ms\n460:\tlearn: 0.3059923\ttotal: 630ms\tremaining: 737ms\n461:\tlearn: 0.3058502\ttotal: 632ms\tremaining: 736ms\n462:\tlearn: 0.3056956\ttotal: 633ms\tremaining: 735ms\n463:\tlearn: 0.3055300\ttotal: 635ms\tremaining: 733ms\n464:\tlearn: 0.3053668\ttotal: 636ms\tremaining: 732ms\n465:\tlearn: 0.3052509\ttotal: 637ms\tremaining: 730ms\n466:\tlearn: 0.3051311\ttotal: 639ms\tremaining: 729ms\n467:\tlearn: 0.3049717\ttotal: 640ms\tremaining: 727ms\n468:\tlearn: 0.3046705\ttotal: 641ms\tremaining: 726ms\n469:\tlearn: 0.3044311\ttotal: 643ms\tremaining: 725ms\n470:\tlearn: 0.3042926\ttotal: 644ms\tremaining: 723ms\n471:\tlearn: 0.3040725\ttotal: 645ms\tremaining: 722ms\n472:\tlearn: 0.3038213\ttotal: 647ms\tremaining: 720ms\n473:\tlearn: 0.3036048\ttotal: 648ms\tremaining: 719ms\n474:\tlearn: 0.3034112\ttotal: 649ms\tremaining: 718ms\n475:\tlearn: 0.3032099\ttotal: 651ms\tremaining: 716ms\n476:\tlearn: 0.3030166\ttotal: 652ms\tremaining: 715ms\n477:\tlearn: 0.3028528\ttotal: 653ms\tremaining: 713ms\n478:\tlearn: 0.3026546\ttotal: 654ms\tremaining: 712ms\n479:\tlearn: 0.3025205\ttotal: 656ms\tremaining: 710ms\n480:\tlearn: 0.3023115\ttotal: 657ms\tremaining: 709ms\n481:\tlearn: 0.3020713\ttotal: 658ms\tremaining: 707ms\n482:\tlearn: 0.3019294\ttotal: 659ms\tremaining: 706ms\n483:\tlearn: 0.3017173\ttotal: 661ms\tremaining: 704ms\n484:\tlearn: 0.3015662\ttotal: 662ms\tremaining: 703ms\n485:\tlearn: 0.3014400\ttotal: 663ms\tremaining: 702ms\n486:\tlearn: 0.3011866\ttotal: 665ms\tremaining: 700ms\n487:\tlearn: 0.3010180\ttotal: 666ms\tremaining: 699ms\n488:\tlearn: 0.3008270\ttotal: 667ms\tremaining: 697ms\n489:\tlearn: 0.3006188\ttotal: 668ms\tremaining: 696ms\n490:\tlearn: 0.3004381\ttotal: 670ms\tremaining: 694ms\n491:\tlearn: 0.3002576\ttotal: 671ms\tremaining: 693ms\n492:\tlearn: 0.3001035\ttotal: 672ms\tremaining: 691ms\n493:\tlearn: 0.2999499\ttotal: 674ms\tremaining: 690ms\n494:\tlearn: 0.2998038\ttotal: 675ms\tremaining: 689ms\n495:\tlearn: 0.2996552\ttotal: 677ms\tremaining: 687ms\n496:\tlearn: 0.2995609\ttotal: 678ms\tremaining: 686ms\n497:\tlearn: 0.2993399\ttotal: 679ms\tremaining: 685ms\n498:\tlearn: 0.2991290\ttotal: 681ms\tremaining: 683ms\n499:\tlearn: 0.2989929\ttotal: 682ms\tremaining: 682ms\n500:\tlearn: 0.2988133\ttotal: 683ms\tremaining: 681ms\n501:\tlearn: 0.2988077\ttotal: 684ms\tremaining: 679ms\n502:\tlearn: 0.2986237\ttotal: 686ms\tremaining: 678ms\n503:\tlearn: 0.2985032\ttotal: 687ms\tremaining: 676ms\n504:\tlearn: 0.2983225\ttotal: 688ms\tremaining: 675ms\n505:\tlearn: 0.2981938\ttotal: 690ms\tremaining: 673ms\n506:\tlearn: 0.2980074\ttotal: 691ms\tremaining: 672ms\n507:\tlearn: 0.2978381\ttotal: 693ms\tremaining: 671ms\n508:\tlearn: 0.2975839\ttotal: 694ms\tremaining: 669ms\n509:\tlearn: 0.2974784\ttotal: 695ms\tremaining: 668ms\n510:\tlearn: 0.2972939\ttotal: 696ms\tremaining: 666ms\n511:\tlearn: 0.2971314\ttotal: 698ms\tremaining: 665ms\n512:\tlearn: 0.2968813\ttotal: 699ms\tremaining: 664ms\n513:\tlearn: 0.2967325\ttotal: 700ms\tremaining: 662ms\n514:\tlearn: 0.2965454\ttotal: 702ms\tremaining: 661ms\n515:\tlearn: 0.2962539\ttotal: 703ms\tremaining: 659ms\n516:\tlearn: 0.2960436\ttotal: 704ms\tremaining: 658ms\n517:\tlearn: 0.2959016\ttotal: 705ms\tremaining: 656ms\n518:\tlearn: 0.2957332\ttotal: 707ms\tremaining: 655ms\n519:\tlearn: 0.2955595\ttotal: 708ms\tremaining: 653ms\n520:\tlearn: 0.2953197\ttotal: 709ms\tremaining: 652ms\n521:\tlearn: 0.2951845\ttotal: 710ms\tremaining: 651ms\n522:\tlearn: 0.2950628\ttotal: 712ms\tremaining: 649ms\n523:\tlearn: 0.2949075\ttotal: 713ms\tremaining: 648ms\n524:\tlearn: 0.2947625\ttotal: 714ms\tremaining: 646ms\n525:\tlearn: 0.2946216\ttotal: 716ms\tremaining: 645ms\n526:\tlearn: 0.2945147\ttotal: 717ms\tremaining: 644ms\n527:\tlearn: 0.2942964\ttotal: 718ms\tremaining: 642ms\n528:\tlearn: 0.2941423\ttotal: 720ms\tremaining: 641ms\n529:\tlearn: 0.2939525\ttotal: 721ms\tremaining: 639ms\n530:\tlearn: 0.2937412\ttotal: 722ms\tremaining: 638ms\n531:\tlearn: 0.2935794\ttotal: 724ms\tremaining: 636ms\n532:\tlearn: 0.2932461\ttotal: 725ms\tremaining: 635ms\n533:\tlearn: 0.2930485\ttotal: 726ms\tremaining: 634ms\n534:\tlearn: 0.2929229\ttotal: 727ms\tremaining: 632ms\n535:\tlearn: 0.2927446\ttotal: 729ms\tremaining: 631ms\n536:\tlearn: 0.2925726\ttotal: 730ms\tremaining: 629ms\n537:\tlearn: 0.2923360\ttotal: 731ms\tremaining: 628ms\n538:\tlearn: 0.2922029\ttotal: 732ms\tremaining: 626ms\n539:\tlearn: 0.2920647\ttotal: 734ms\tremaining: 625ms\n540:\tlearn: 0.2919557\ttotal: 735ms\tremaining: 623ms\n541:\tlearn: 0.2917632\ttotal: 736ms\tremaining: 622ms\n542:\tlearn: 0.2915359\ttotal: 738ms\tremaining: 621ms\n543:\tlearn: 0.2913527\ttotal: 739ms\tremaining: 619ms\n544:\tlearn: 0.2911830\ttotal: 740ms\tremaining: 618ms\n545:\tlearn: 0.2909596\ttotal: 742ms\tremaining: 617ms\n546:\tlearn: 0.2908098\ttotal: 743ms\tremaining: 615ms\n547:\tlearn: 0.2906936\ttotal: 744ms\tremaining: 614ms\n548:\tlearn: 0.2905236\ttotal: 746ms\tremaining: 613ms\n549:\tlearn: 0.2903478\ttotal: 748ms\tremaining: 612ms\n550:\tlearn: 0.2902190\ttotal: 749ms\tremaining: 611ms\n551:\tlearn: 0.2900984\ttotal: 750ms\tremaining: 609ms\n552:\tlearn: 0.2898902\ttotal: 752ms\tremaining: 608ms\n553:\tlearn: 0.2897362\ttotal: 753ms\tremaining: 606ms\n554:\tlearn: 0.2895528\ttotal: 754ms\tremaining: 605ms\n555:\tlearn: 0.2893705\ttotal: 756ms\tremaining: 603ms\n556:\tlearn: 0.2891897\ttotal: 757ms\tremaining: 602ms\n557:\tlearn: 0.2890448\ttotal: 758ms\tremaining: 601ms\n558:\tlearn: 0.2889301\ttotal: 759ms\tremaining: 599ms\n559:\tlearn: 0.2887452\ttotal: 761ms\tremaining: 598ms\n560:\tlearn: 0.2885873\ttotal: 762ms\tremaining: 596ms\n561:\tlearn: 0.2884275\ttotal: 763ms\tremaining: 595ms\n562:\tlearn: 0.2881778\ttotal: 764ms\tremaining: 593ms\n563:\tlearn: 0.2880175\ttotal: 766ms\tremaining: 592ms\n564:\tlearn: 0.2878475\ttotal: 767ms\tremaining: 591ms\n565:\tlearn: 0.2877268\ttotal: 769ms\tremaining: 589ms\n566:\tlearn: 0.2875861\ttotal: 770ms\tremaining: 588ms\n567:\tlearn: 0.2874348\ttotal: 771ms\tremaining: 586ms\n568:\tlearn: 0.2872822\ttotal: 772ms\tremaining: 585ms\n569:\tlearn: 0.2870548\ttotal: 774ms\tremaining: 584ms\n570:\tlearn: 0.2867685\ttotal: 775ms\tremaining: 582ms\n571:\tlearn: 0.2866067\ttotal: 776ms\tremaining: 581ms\n572:\tlearn: 0.2864157\ttotal: 777ms\tremaining: 579ms\n573:\tlearn: 0.2864108\ttotal: 778ms\tremaining: 578ms\n574:\tlearn: 0.2862589\ttotal: 780ms\tremaining: 576ms\n575:\tlearn: 0.2861226\ttotal: 781ms\tremaining: 575ms\n576:\tlearn: 0.2858864\ttotal: 782ms\tremaining: 573ms\n577:\tlearn: 0.2857049\ttotal: 784ms\tremaining: 572ms\n578:\tlearn: 0.2854759\ttotal: 785ms\tremaining: 571ms\n579:\tlearn: 0.2854682\ttotal: 786ms\tremaining: 569ms\n580:\tlearn: 0.2852976\ttotal: 787ms\tremaining: 568ms\n581:\tlearn: 0.2851420\ttotal: 789ms\tremaining: 566ms\n582:\tlearn: 0.2850045\ttotal: 790ms\tremaining: 565ms\n583:\tlearn: 0.2847854\ttotal: 791ms\tremaining: 564ms\n584:\tlearn: 0.2844940\ttotal: 793ms\tremaining: 562ms\n585:\tlearn: 0.2842732\ttotal: 794ms\tremaining: 561ms\n586:\tlearn: 0.2841619\ttotal: 795ms\tremaining: 559ms\n587:\tlearn: 0.2839890\ttotal: 796ms\tremaining: 558ms\n588:\tlearn: 0.2838209\ttotal: 798ms\tremaining: 557ms\n589:\tlearn: 0.2836811\ttotal: 799ms\tremaining: 555ms\n590:\tlearn: 0.2835101\ttotal: 800ms\tremaining: 554ms\n591:\tlearn: 0.2833723\ttotal: 802ms\tremaining: 552ms\n592:\tlearn: 0.2831506\ttotal: 803ms\tremaining: 551ms\n593:\tlearn: 0.2829968\ttotal: 804ms\tremaining: 550ms\n594:\tlearn: 0.2828125\ttotal: 805ms\tremaining: 548ms\n595:\tlearn: 0.2826944\ttotal: 807ms\tremaining: 547ms\n596:\tlearn: 0.2824992\ttotal: 808ms\tremaining: 545ms\n597:\tlearn: 0.2822401\ttotal: 809ms\tremaining: 544ms\n598:\tlearn: 0.2819873\ttotal: 811ms\tremaining: 543ms\n599:\tlearn: 0.2817665\ttotal: 812ms\tremaining: 541ms\n600:\tlearn: 0.2815971\ttotal: 813ms\tremaining: 540ms\n601:\tlearn: 0.2814480\ttotal: 814ms\tremaining: 538ms\n602:\tlearn: 0.2811856\ttotal: 816ms\tremaining: 537ms\n603:\tlearn: 0.2810008\ttotal: 817ms\tremaining: 536ms\n604:\tlearn: 0.2807857\ttotal: 818ms\tremaining: 534ms\n605:\tlearn: 0.2806468\ttotal: 820ms\tremaining: 533ms\n606:\tlearn: 0.2805099\ttotal: 821ms\tremaining: 531ms\n607:\tlearn: 0.2803619\ttotal: 822ms\tremaining: 530ms\n608:\tlearn: 0.2801597\ttotal: 823ms\tremaining: 529ms\n609:\tlearn: 0.2800139\ttotal: 825ms\tremaining: 527ms\n610:\tlearn: 0.2798046\ttotal: 826ms\tremaining: 526ms\n611:\tlearn: 0.2796424\ttotal: 827ms\tremaining: 524ms\n612:\tlearn: 0.2794853\ttotal: 828ms\tremaining: 523ms\n613:\tlearn: 0.2792925\ttotal: 830ms\tremaining: 521ms\n614:\tlearn: 0.2791354\ttotal: 831ms\tremaining: 520ms\n615:\tlearn: 0.2789958\ttotal: 832ms\tremaining: 519ms\n616:\tlearn: 0.2788063\ttotal: 833ms\tremaining: 517ms\n617:\tlearn: 0.2786400\ttotal: 834ms\tremaining: 516ms\n618:\tlearn: 0.2785140\ttotal: 836ms\tremaining: 514ms\n619:\tlearn: 0.2783569\ttotal: 837ms\tremaining: 513ms\n620:\tlearn: 0.2781239\ttotal: 838ms\tremaining: 512ms\n621:\tlearn: 0.2781215\ttotal: 839ms\tremaining: 510ms\n622:\tlearn: 0.2779133\ttotal: 840ms\tremaining: 509ms\n623:\tlearn: 0.2777607\ttotal: 842ms\tremaining: 507ms\n624:\tlearn: 0.2775664\ttotal: 843ms\tremaining: 506ms\n625:\tlearn: 0.2774211\ttotal: 844ms\tremaining: 504ms\n626:\tlearn: 0.2772632\ttotal: 846ms\tremaining: 503ms\n627:\tlearn: 0.2770905\ttotal: 847ms\tremaining: 502ms\n628:\tlearn: 0.2769051\ttotal: 848ms\tremaining: 500ms\n629:\tlearn: 0.2767749\ttotal: 849ms\tremaining: 499ms\n630:\tlearn: 0.2765253\ttotal: 851ms\tremaining: 498ms\n631:\tlearn: 0.2763193\ttotal: 852ms\tremaining: 496ms\n632:\tlearn: 0.2760831\ttotal: 854ms\tremaining: 495ms\n633:\tlearn: 0.2759096\ttotal: 855ms\tremaining: 494ms\n634:\tlearn: 0.2757282\ttotal: 857ms\tremaining: 492ms\n635:\tlearn: 0.2755605\ttotal: 858ms\tremaining: 491ms\n636:\tlearn: 0.2754263\ttotal: 859ms\tremaining: 490ms\n637:\tlearn: 0.2752885\ttotal: 860ms\tremaining: 488ms\n638:\tlearn: 0.2751041\ttotal: 862ms\tremaining: 487ms\n639:\tlearn: 0.2749064\ttotal: 863ms\tremaining: 486ms\n640:\tlearn: 0.2746700\ttotal: 865ms\tremaining: 484ms\n641:\tlearn: 0.2745215\ttotal: 866ms\tremaining: 483ms\n642:\tlearn: 0.2744073\ttotal: 868ms\tremaining: 482ms\n643:\tlearn: 0.2742254\ttotal: 869ms\tremaining: 480ms\n644:\tlearn: 0.2740165\ttotal: 870ms\tremaining: 479ms\n645:\tlearn: 0.2739000\ttotal: 872ms\tremaining: 478ms\n646:\tlearn: 0.2737322\ttotal: 873ms\tremaining: 476ms\n647:\tlearn: 0.2735602\ttotal: 874ms\tremaining: 475ms\n648:\tlearn: 0.2734075\ttotal: 875ms\tremaining: 473ms\n649:\tlearn: 0.2732657\ttotal: 877ms\tremaining: 472ms\n650:\tlearn: 0.2731144\ttotal: 878ms\tremaining: 471ms\n651:\tlearn: 0.2729493\ttotal: 879ms\tremaining: 469ms\n652:\tlearn: 0.2727507\ttotal: 881ms\tremaining: 468ms\n653:\tlearn: 0.2725912\ttotal: 882ms\tremaining: 467ms\n654:\tlearn: 0.2724875\ttotal: 883ms\tremaining: 465ms\n655:\tlearn: 0.2723055\ttotal: 885ms\tremaining: 464ms\n656:\tlearn: 0.2721795\ttotal: 886ms\tremaining: 462ms\n657:\tlearn: 0.2720429\ttotal: 887ms\tremaining: 461ms\n658:\tlearn: 0.2718504\ttotal: 888ms\tremaining: 460ms\n659:\tlearn: 0.2717093\ttotal: 890ms\tremaining: 458ms\n660:\tlearn: 0.2715647\ttotal: 891ms\tremaining: 457ms\n661:\tlearn: 0.2714193\ttotal: 892ms\tremaining: 456ms\n662:\tlearn: 0.2712147\ttotal: 893ms\tremaining: 454ms\n663:\tlearn: 0.2710933\ttotal: 895ms\tremaining: 453ms\n664:\tlearn: 0.2708801\ttotal: 896ms\tremaining: 451ms\n665:\tlearn: 0.2707377\ttotal: 897ms\tremaining: 450ms\n666:\tlearn: 0.2705821\ttotal: 898ms\tremaining: 449ms\n667:\tlearn: 0.2704057\ttotal: 900ms\tremaining: 447ms\n668:\tlearn: 0.2702309\ttotal: 901ms\tremaining: 446ms\n669:\tlearn: 0.2700340\ttotal: 902ms\tremaining: 444ms\n670:\tlearn: 0.2698945\ttotal: 904ms\tremaining: 443ms\n671:\tlearn: 0.2697308\ttotal: 905ms\tremaining: 442ms\n672:\tlearn: 0.2695605\ttotal: 906ms\tremaining: 440ms\n673:\tlearn: 0.2693502\ttotal: 907ms\tremaining: 439ms\n674:\tlearn: 0.2692143\ttotal: 909ms\tremaining: 438ms\n675:\tlearn: 0.2690329\ttotal: 910ms\tremaining: 436ms\n676:\tlearn: 0.2688854\ttotal: 911ms\tremaining: 435ms\n677:\tlearn: 0.2687502\ttotal: 913ms\tremaining: 433ms\n678:\tlearn: 0.2686358\ttotal: 914ms\tremaining: 432ms\n679:\tlearn: 0.2685010\ttotal: 915ms\tremaining: 431ms\n680:\tlearn: 0.2683418\ttotal: 916ms\tremaining: 429ms\n681:\tlearn: 0.2682146\ttotal: 918ms\tremaining: 428ms\n682:\tlearn: 0.2680718\ttotal: 919ms\tremaining: 426ms\n683:\tlearn: 0.2679366\ttotal: 920ms\tremaining: 425ms\n684:\tlearn: 0.2677370\ttotal: 921ms\tremaining: 424ms\n685:\tlearn: 0.2675566\ttotal: 923ms\tremaining: 422ms\n686:\tlearn: 0.2673894\ttotal: 924ms\tremaining: 421ms\n687:\tlearn: 0.2672498\ttotal: 925ms\tremaining: 420ms\n688:\tlearn: 0.2671363\ttotal: 926ms\tremaining: 418ms\n689:\tlearn: 0.2670043\ttotal: 928ms\tremaining: 417ms\n690:\tlearn: 0.2668368\ttotal: 929ms\tremaining: 415ms\n691:\tlearn: 0.2666707\ttotal: 930ms\tremaining: 414ms\n692:\tlearn: 0.2665714\ttotal: 932ms\tremaining: 413ms\n693:\tlearn: 0.2664364\ttotal: 933ms\tremaining: 411ms\n694:\tlearn: 0.2662776\ttotal: 935ms\tremaining: 410ms\n695:\tlearn: 0.2661164\ttotal: 936ms\tremaining: 409ms\n696:\tlearn: 0.2659506\ttotal: 937ms\tremaining: 408ms\n697:\tlearn: 0.2658006\ttotal: 939ms\tremaining: 406ms\n698:\tlearn: 0.2656033\ttotal: 940ms\tremaining: 405ms\n699:\tlearn: 0.2654248\ttotal: 942ms\tremaining: 404ms\n700:\tlearn: 0.2652839\ttotal: 943ms\tremaining: 402ms\n701:\tlearn: 0.2651159\ttotal: 944ms\tremaining: 401ms\n702:\tlearn: 0.2649314\ttotal: 946ms\tremaining: 399ms\n703:\tlearn: 0.2647537\ttotal: 947ms\tremaining: 398ms\n704:\tlearn: 0.2646088\ttotal: 948ms\tremaining: 397ms\n705:\tlearn: 0.2644970\ttotal: 949ms\tremaining: 395ms\n706:\tlearn: 0.2643188\ttotal: 951ms\tremaining: 394ms\n707:\tlearn: 0.2641252\ttotal: 952ms\tremaining: 393ms\n708:\tlearn: 0.2640359\ttotal: 953ms\tremaining: 391ms\n709:\tlearn: 0.2639199\ttotal: 954ms\tremaining: 390ms\n710:\tlearn: 0.2637750\ttotal: 956ms\tremaining: 388ms\n711:\tlearn: 0.2635847\ttotal: 957ms\tremaining: 387ms\n712:\tlearn: 0.2633960\ttotal: 958ms\tremaining: 386ms\n713:\tlearn: 0.2632343\ttotal: 959ms\tremaining: 384ms\n714:\tlearn: 0.2630984\ttotal: 961ms\tremaining: 383ms\n715:\tlearn: 0.2629790\ttotal: 962ms\tremaining: 382ms\n716:\tlearn: 0.2628442\ttotal: 963ms\tremaining: 380ms\n717:\tlearn: 0.2626876\ttotal: 965ms\tremaining: 379ms\n718:\tlearn: 0.2624853\ttotal: 966ms\tremaining: 377ms\n719:\tlearn: 0.2623398\ttotal: 967ms\tremaining: 376ms\n720:\tlearn: 0.2622274\ttotal: 968ms\tremaining: 375ms\n721:\tlearn: 0.2619933\ttotal: 970ms\tremaining: 373ms\n722:\tlearn: 0.2618562\ttotal: 971ms\tremaining: 372ms\n723:\tlearn: 0.2616724\ttotal: 972ms\tremaining: 371ms\n724:\tlearn: 0.2615328\ttotal: 974ms\tremaining: 369ms\n725:\tlearn: 0.2613417\ttotal: 975ms\tremaining: 368ms\n726:\tlearn: 0.2612160\ttotal: 977ms\tremaining: 367ms\n727:\tlearn: 0.2610727\ttotal: 978ms\tremaining: 365ms\n728:\tlearn: 0.2609397\ttotal: 979ms\tremaining: 364ms\n729:\tlearn: 0.2608150\ttotal: 980ms\tremaining: 363ms\n730:\tlearn: 0.2606940\ttotal: 982ms\tremaining: 361ms\n731:\tlearn: 0.2605297\ttotal: 983ms\tremaining: 360ms\n732:\tlearn: 0.2603439\ttotal: 985ms\tremaining: 359ms\n733:\tlearn: 0.2602117\ttotal: 986ms\tremaining: 357ms\n734:\tlearn: 0.2600208\ttotal: 987ms\tremaining: 356ms\n735:\tlearn: 0.2599040\ttotal: 989ms\tremaining: 355ms\n736:\tlearn: 0.2597566\ttotal: 990ms\tremaining: 353ms\n737:\tlearn: 0.2596297\ttotal: 991ms\tremaining: 352ms\n738:\tlearn: 0.2595039\ttotal: 993ms\tremaining: 351ms\n739:\tlearn: 0.2593529\ttotal: 994ms\tremaining: 349ms\n740:\tlearn: 0.2591722\ttotal: 995ms\tremaining: 348ms\n741:\tlearn: 0.2589801\ttotal: 997ms\tremaining: 347ms\n742:\tlearn: 0.2587950\ttotal: 998ms\tremaining: 345ms\n743:\tlearn: 0.2586596\ttotal: 999ms\tremaining: 344ms\n744:\tlearn: 0.2585278\ttotal: 1s\tremaining: 342ms\n745:\tlearn: 0.2584181\ttotal: 1s\tremaining: 341ms\n746:\tlearn: 0.2582351\ttotal: 1s\tremaining: 340ms\n747:\tlearn: 0.2580539\ttotal: 1s\tremaining: 338ms\n748:\tlearn: 0.2578629\ttotal: 1s\tremaining: 337ms\n749:\tlearn: 0.2576646\ttotal: 1.01s\tremaining: 336ms\n750:\tlearn: 0.2575551\ttotal: 1.01s\tremaining: 334ms\n751:\tlearn: 0.2573615\ttotal: 1.01s\tremaining: 333ms\n752:\tlearn: 0.2571761\ttotal: 1.01s\tremaining: 332ms\n753:\tlearn: 0.2569959\ttotal: 1.01s\tremaining: 330ms\n754:\tlearn: 0.2568631\ttotal: 1.01s\tremaining: 329ms\n755:\tlearn: 0.2566885\ttotal: 1.01s\tremaining: 327ms\n756:\tlearn: 0.2565213\ttotal: 1.01s\tremaining: 326ms\n757:\tlearn: 0.2563737\ttotal: 1.02s\tremaining: 325ms\n758:\tlearn: 0.2561886\ttotal: 1.02s\tremaining: 324ms\n759:\tlearn: 0.2560190\ttotal: 1.02s\tremaining: 322ms\n760:\tlearn: 0.2558421\ttotal: 1.02s\tremaining: 321ms\n761:\tlearn: 0.2557115\ttotal: 1.02s\tremaining: 320ms\n762:\tlearn: 0.2555401\ttotal: 1.02s\tremaining: 318ms\n763:\tlearn: 0.2553786\ttotal: 1.03s\tremaining: 317ms\n764:\tlearn: 0.2551915\ttotal: 1.03s\tremaining: 316ms\n765:\tlearn: 0.2550035\ttotal: 1.03s\tremaining: 314ms\n766:\tlearn: 0.2548237\ttotal: 1.03s\tremaining: 313ms\n767:\tlearn: 0.2547038\ttotal: 1.03s\tremaining: 312ms\n768:\tlearn: 0.2545564\ttotal: 1.03s\tremaining: 311ms\n769:\tlearn: 0.2544045\ttotal: 1.03s\tremaining: 309ms\n770:\tlearn: 0.2542303\ttotal: 1.04s\tremaining: 308ms\n771:\tlearn: 0.2540661\ttotal: 1.04s\tremaining: 306ms\n772:\tlearn: 0.2539300\ttotal: 1.04s\tremaining: 305ms\n773:\tlearn: 0.2538359\ttotal: 1.04s\tremaining: 304ms\n774:\tlearn: 0.2536568\ttotal: 1.04s\tremaining: 302ms\n775:\tlearn: 0.2534452\ttotal: 1.04s\tremaining: 301ms\n776:\tlearn: 0.2533192\ttotal: 1.04s\tremaining: 300ms\n777:\tlearn: 0.2531626\ttotal: 1.04s\tremaining: 298ms\n778:\tlearn: 0.2529962\ttotal: 1.05s\tremaining: 297ms\n779:\tlearn: 0.2528201\ttotal: 1.05s\tremaining: 296ms\n780:\tlearn: 0.2526695\ttotal: 1.05s\tremaining: 294ms\n781:\tlearn: 0.2525457\ttotal: 1.05s\tremaining: 293ms\n782:\tlearn: 0.2523864\ttotal: 1.05s\tremaining: 292ms\n783:\tlearn: 0.2521857\ttotal: 1.05s\tremaining: 290ms\n784:\tlearn: 0.2520758\ttotal: 1.05s\tremaining: 289ms\n785:\tlearn: 0.2519207\ttotal: 1.06s\tremaining: 288ms\n786:\tlearn: 0.2517888\ttotal: 1.06s\tremaining: 286ms\n787:\tlearn: 0.2516184\ttotal: 1.06s\tremaining: 285ms\n788:\tlearn: 0.2514765\ttotal: 1.06s\tremaining: 284ms\n789:\tlearn: 0.2512973\ttotal: 1.06s\tremaining: 282ms\n790:\tlearn: 0.2511322\ttotal: 1.06s\tremaining: 281ms\n791:\tlearn: 0.2510109\ttotal: 1.06s\tremaining: 280ms\n792:\tlearn: 0.2508819\ttotal: 1.07s\tremaining: 278ms\n793:\tlearn: 0.2507410\ttotal: 1.07s\tremaining: 277ms\n794:\tlearn: 0.2506057\ttotal: 1.07s\tremaining: 276ms\n795:\tlearn: 0.2504359\ttotal: 1.07s\tremaining: 274ms\n796:\tlearn: 0.2502848\ttotal: 1.07s\tremaining: 273ms\n797:\tlearn: 0.2501274\ttotal: 1.07s\tremaining: 272ms\n798:\tlearn: 0.2499878\ttotal: 1.07s\tremaining: 270ms\n799:\tlearn: 0.2498258\ttotal: 1.07s\tremaining: 269ms\n800:\tlearn: 0.2496946\ttotal: 1.08s\tremaining: 268ms\n801:\tlearn: 0.2495761\ttotal: 1.08s\tremaining: 266ms\n802:\tlearn: 0.2494644\ttotal: 1.08s\tremaining: 265ms\n803:\tlearn: 0.2493376\ttotal: 1.08s\tremaining: 264ms\n804:\tlearn: 0.2491850\ttotal: 1.08s\tremaining: 262ms\n805:\tlearn: 0.2490135\ttotal: 1.08s\tremaining: 261ms\n806:\tlearn: 0.2488999\ttotal: 1.08s\tremaining: 259ms\n807:\tlearn: 0.2487890\ttotal: 1.09s\tremaining: 258ms\n808:\tlearn: 0.2486602\ttotal: 1.09s\tremaining: 257ms\n809:\tlearn: 0.2485331\ttotal: 1.09s\tremaining: 255ms\n810:\tlearn: 0.2483890\ttotal: 1.09s\tremaining: 254ms\n811:\tlearn: 0.2482359\ttotal: 1.09s\tremaining: 253ms\n812:\tlearn: 0.2481331\ttotal: 1.09s\tremaining: 251ms\n813:\tlearn: 0.2480208\ttotal: 1.09s\tremaining: 250ms\n814:\tlearn: 0.2478257\ttotal: 1.09s\tremaining: 249ms\n815:\tlearn: 0.2477161\ttotal: 1.1s\tremaining: 247ms\n816:\tlearn: 0.2476005\ttotal: 1.1s\tremaining: 246ms\n817:\tlearn: 0.2474556\ttotal: 1.1s\tremaining: 245ms\n818:\tlearn: 0.2473117\ttotal: 1.1s\tremaining: 243ms\n819:\tlearn: 0.2471438\ttotal: 1.1s\tremaining: 242ms\n820:\tlearn: 0.2470110\ttotal: 1.1s\tremaining: 241ms\n821:\tlearn: 0.2468662\ttotal: 1.1s\tremaining: 239ms\n822:\tlearn: 0.2466892\ttotal: 1.1s\tremaining: 238ms\n823:\tlearn: 0.2465174\ttotal: 1.11s\tremaining: 236ms\n824:\tlearn: 0.2463537\ttotal: 1.11s\tremaining: 235ms\n825:\tlearn: 0.2462154\ttotal: 1.11s\tremaining: 234ms\n826:\tlearn: 0.2460792\ttotal: 1.11s\tremaining: 232ms\n827:\tlearn: 0.2459665\ttotal: 1.11s\tremaining: 231ms\n828:\tlearn: 0.2458265\ttotal: 1.11s\tremaining: 230ms\n829:\tlearn: 0.2456899\ttotal: 1.11s\tremaining: 228ms\n830:\tlearn: 0.2455170\ttotal: 1.11s\tremaining: 227ms\n831:\tlearn: 0.2453429\ttotal: 1.12s\tremaining: 226ms\n832:\tlearn: 0.2452208\ttotal: 1.12s\tremaining: 224ms\n833:\tlearn: 0.2451141\ttotal: 1.12s\tremaining: 223ms\n834:\tlearn: 0.2449364\ttotal: 1.12s\tremaining: 221ms\n835:\tlearn: 0.2447844\ttotal: 1.12s\tremaining: 220ms\n836:\tlearn: 0.2446251\ttotal: 1.12s\tremaining: 219ms\n837:\tlearn: 0.2444965\ttotal: 1.13s\tremaining: 218ms\n838:\tlearn: 0.2443039\ttotal: 1.13s\tremaining: 216ms\n839:\tlearn: 0.2441645\ttotal: 1.13s\tremaining: 215ms\n840:\tlearn: 0.2440399\ttotal: 1.13s\tremaining: 214ms\n841:\tlearn: 0.2438619\ttotal: 1.13s\tremaining: 212ms\n842:\tlearn: 0.2437294\ttotal: 1.13s\tremaining: 211ms\n843:\tlearn: 0.2435935\ttotal: 1.13s\tremaining: 209ms\n844:\tlearn: 0.2434894\ttotal: 1.13s\tremaining: 208ms\n845:\tlearn: 0.2433041\ttotal: 1.14s\tremaining: 207ms\n846:\tlearn: 0.2431869\ttotal: 1.14s\tremaining: 205ms\n847:\tlearn: 0.2430468\ttotal: 1.14s\tremaining: 204ms\n848:\tlearn: 0.2428883\ttotal: 1.14s\tremaining: 203ms\n849:\tlearn: 0.2427056\ttotal: 1.14s\tremaining: 201ms\n850:\tlearn: 0.2425583\ttotal: 1.14s\tremaining: 200ms\n851:\tlearn: 0.2424505\ttotal: 1.14s\tremaining: 199ms\n852:\tlearn: 0.2423473\ttotal: 1.14s\tremaining: 197ms\n853:\tlearn: 0.2421961\ttotal: 1.15s\tremaining: 196ms\n854:\tlearn: 0.2420752\ttotal: 1.15s\tremaining: 195ms\n855:\tlearn: 0.2419252\ttotal: 1.15s\tremaining: 193ms\n856:\tlearn: 0.2417955\ttotal: 1.15s\tremaining: 192ms\n857:\tlearn: 0.2416949\ttotal: 1.15s\tremaining: 191ms\n858:\tlearn: 0.2415842\ttotal: 1.15s\tremaining: 189ms\n859:\tlearn: 0.2414533\ttotal: 1.15s\tremaining: 188ms\n860:\tlearn: 0.2413509\ttotal: 1.15s\tremaining: 186ms\n861:\tlearn: 0.2412500\ttotal: 1.16s\tremaining: 185ms\n862:\tlearn: 0.2411418\ttotal: 1.16s\tremaining: 184ms\n863:\tlearn: 0.2409877\ttotal: 1.16s\tremaining: 182ms\n864:\tlearn: 0.2408537\ttotal: 1.16s\tremaining: 181ms\n865:\tlearn: 0.2407417\ttotal: 1.16s\tremaining: 180ms\n866:\tlearn: 0.2406174\ttotal: 1.16s\tremaining: 178ms\n867:\tlearn: 0.2404251\ttotal: 1.16s\tremaining: 177ms\n868:\tlearn: 0.2402592\ttotal: 1.17s\tremaining: 176ms\n869:\tlearn: 0.2401515\ttotal: 1.17s\tremaining: 174ms\n870:\tlearn: 0.2400274\ttotal: 1.17s\tremaining: 173ms\n871:\tlearn: 0.2398506\ttotal: 1.17s\tremaining: 172ms\n872:\tlearn: 0.2397343\ttotal: 1.17s\tremaining: 170ms\n873:\tlearn: 0.2395966\ttotal: 1.17s\tremaining: 169ms\n874:\tlearn: 0.2394352\ttotal: 1.17s\tremaining: 168ms\n875:\tlearn: 0.2393079\ttotal: 1.17s\tremaining: 166ms\n876:\tlearn: 0.2392096\ttotal: 1.18s\tremaining: 165ms\n877:\tlearn: 0.2390577\ttotal: 1.18s\tremaining: 164ms\n878:\tlearn: 0.2389752\ttotal: 1.18s\tremaining: 162ms\n879:\tlearn: 0.2388773\ttotal: 1.18s\tremaining: 161ms\n880:\tlearn: 0.2387703\ttotal: 1.18s\tremaining: 160ms\n881:\tlearn: 0.2385955\ttotal: 1.18s\tremaining: 158ms\n882:\tlearn: 0.2384377\ttotal: 1.18s\tremaining: 157ms\n883:\tlearn: 0.2383398\ttotal: 1.19s\tremaining: 156ms\n884:\tlearn: 0.2381853\ttotal: 1.19s\tremaining: 154ms\n885:\tlearn: 0.2380371\ttotal: 1.19s\tremaining: 153ms\n886:\tlearn: 0.2379206\ttotal: 1.19s\tremaining: 151ms\n887:\tlearn: 0.2377223\ttotal: 1.19s\tremaining: 150ms\n888:\tlearn: 0.2376358\ttotal: 1.19s\tremaining: 149ms\n889:\tlearn: 0.2374768\ttotal: 1.19s\tremaining: 147ms\n890:\tlearn: 0.2373863\ttotal: 1.19s\tremaining: 146ms\n891:\tlearn: 0.2372932\ttotal: 1.2s\tremaining: 145ms\n892:\tlearn: 0.2371005\ttotal: 1.2s\tremaining: 143ms\n893:\tlearn: 0.2369937\ttotal: 1.2s\tremaining: 142ms\n894:\tlearn: 0.2368395\ttotal: 1.2s\tremaining: 141ms\n895:\tlearn: 0.2367441\ttotal: 1.2s\tremaining: 139ms\n896:\tlearn: 0.2366415\ttotal: 1.2s\tremaining: 138ms\n897:\tlearn: 0.2365279\ttotal: 1.2s\tremaining: 137ms\n898:\tlearn: 0.2363687\ttotal: 1.2s\tremaining: 135ms\n899:\tlearn: 0.2362222\ttotal: 1.21s\tremaining: 134ms\n900:\tlearn: 0.2361391\ttotal: 1.21s\tremaining: 133ms\n901:\tlearn: 0.2360159\ttotal: 1.21s\tremaining: 131ms\n902:\tlearn: 0.2359040\ttotal: 1.21s\tremaining: 130ms\n903:\tlearn: 0.2357487\ttotal: 1.21s\tremaining: 129ms\n904:\tlearn: 0.2356280\ttotal: 1.21s\tremaining: 127ms\n905:\tlearn: 0.2354862\ttotal: 1.21s\tremaining: 126ms\n906:\tlearn: 0.2352983\ttotal: 1.21s\tremaining: 125ms\n907:\tlearn: 0.2352044\ttotal: 1.22s\tremaining: 123ms\n908:\tlearn: 0.2350961\ttotal: 1.22s\tremaining: 122ms\n909:\tlearn: 0.2349078\ttotal: 1.22s\tremaining: 121ms\n910:\tlearn: 0.2348008\ttotal: 1.22s\tremaining: 119ms\n911:\tlearn: 0.2346816\ttotal: 1.22s\tremaining: 118ms\n912:\tlearn: 0.2345767\ttotal: 1.22s\tremaining: 117ms\n913:\tlearn: 0.2344968\ttotal: 1.22s\tremaining: 115ms\n914:\tlearn: 0.2344064\ttotal: 1.23s\tremaining: 114ms\n915:\tlearn: 0.2342559\ttotal: 1.23s\tremaining: 112ms\n916:\tlearn: 0.2340730\ttotal: 1.23s\tremaining: 111ms\n917:\tlearn: 0.2339523\ttotal: 1.23s\tremaining: 110ms\n918:\tlearn: 0.2337844\ttotal: 1.23s\tremaining: 108ms\n919:\tlearn: 0.2336549\ttotal: 1.23s\tremaining: 107ms\n920:\tlearn: 0.2335465\ttotal: 1.23s\tremaining: 106ms\n921:\tlearn: 0.2333997\ttotal: 1.23s\tremaining: 104ms\n922:\tlearn: 0.2332310\ttotal: 1.24s\tremaining: 103ms\n923:\tlearn: 0.2330662\ttotal: 1.24s\tremaining: 102ms\n924:\tlearn: 0.2329749\ttotal: 1.24s\tremaining: 100ms\n925:\tlearn: 0.2328288\ttotal: 1.24s\tremaining: 99.1ms\n926:\tlearn: 0.2327016\ttotal: 1.24s\tremaining: 97.7ms\n927:\tlearn: 0.2325844\ttotal: 1.24s\tremaining: 96.4ms\n928:\tlearn: 0.2324867\ttotal: 1.24s\tremaining: 95ms\n929:\tlearn: 0.2323499\ttotal: 1.24s\tremaining: 93.7ms\n930:\tlearn: 0.2321877\ttotal: 1.25s\tremaining: 92.4ms\n931:\tlearn: 0.2320211\ttotal: 1.25s\tremaining: 91ms\n932:\tlearn: 0.2318794\ttotal: 1.25s\tremaining: 89.7ms\n933:\tlearn: 0.2317919\ttotal: 1.25s\tremaining: 88.3ms\n934:\tlearn: 0.2316817\ttotal: 1.25s\tremaining: 87ms\n935:\tlearn: 0.2315785\ttotal: 1.25s\tremaining: 85.7ms\n936:\tlearn: 0.2314369\ttotal: 1.25s\tremaining: 84.3ms\n937:\tlearn: 0.2313316\ttotal: 1.25s\tremaining: 83ms\n938:\tlearn: 0.2311944\ttotal: 1.26s\tremaining: 81.6ms\n939:\tlearn: 0.2310629\ttotal: 1.26s\tremaining: 80.3ms\n940:\tlearn: 0.2308922\ttotal: 1.26s\tremaining: 79ms\n941:\tlearn: 0.2307811\ttotal: 1.26s\tremaining: 77.6ms\n942:\tlearn: 0.2306170\ttotal: 1.26s\tremaining: 76.3ms\n943:\tlearn: 0.2305289\ttotal: 1.26s\tremaining: 74.9ms\n944:\tlearn: 0.2303702\ttotal: 1.26s\tremaining: 73.6ms\n945:\tlearn: 0.2302684\ttotal: 1.26s\tremaining: 72.3ms\n946:\tlearn: 0.2300650\ttotal: 1.27s\tremaining: 70.9ms\n947:\tlearn: 0.2299574\ttotal: 1.27s\tremaining: 69.6ms\n948:\tlearn: 0.2297789\ttotal: 1.27s\tremaining: 68.2ms\n949:\tlearn: 0.2296886\ttotal: 1.27s\tremaining: 66.9ms\n950:\tlearn: 0.2295969\ttotal: 1.27s\tremaining: 65.5ms\n951:\tlearn: 0.2294750\ttotal: 1.27s\tremaining: 64.2ms\n952:\tlearn: 0.2293852\ttotal: 1.27s\tremaining: 62.9ms\n953:\tlearn: 0.2292566\ttotal: 1.28s\tremaining: 61.5ms\n954:\tlearn: 0.2291288\ttotal: 1.28s\tremaining: 60.2ms\n955:\tlearn: 0.2289669\ttotal: 1.28s\tremaining: 58.9ms\n956:\tlearn: 0.2287992\ttotal: 1.28s\tremaining: 57.5ms\n957:\tlearn: 0.2286856\ttotal: 1.28s\tremaining: 56.2ms\n958:\tlearn: 0.2285741\ttotal: 1.28s\tremaining: 54.9ms\n959:\tlearn: 0.2283999\ttotal: 1.28s\tremaining: 53.5ms\n960:\tlearn: 0.2283209\ttotal: 1.28s\tremaining: 52.2ms\n961:\tlearn: 0.2282311\ttotal: 1.29s\tremaining: 50.8ms\n962:\tlearn: 0.2280699\ttotal: 1.29s\tremaining: 49.5ms\n963:\tlearn: 0.2279441\ttotal: 1.29s\tremaining: 48.2ms\n964:\tlearn: 0.2277671\ttotal: 1.29s\tremaining: 46.8ms\n965:\tlearn: 0.2276439\ttotal: 1.29s\tremaining: 45.5ms\n966:\tlearn: 0.2275516\ttotal: 1.29s\tremaining: 44.2ms\n967:\tlearn: 0.2274655\ttotal: 1.29s\tremaining: 42.8ms\n968:\tlearn: 0.2273657\ttotal: 1.3s\tremaining: 41.5ms\n969:\tlearn: 0.2272552\ttotal: 1.3s\tremaining: 40.2ms\n970:\tlearn: 0.2271202\ttotal: 1.3s\tremaining: 38.8ms\n971:\tlearn: 0.2269476\ttotal: 1.3s\tremaining: 37.5ms\n972:\tlearn: 0.2267795\ttotal: 1.3s\tremaining: 36.1ms\n973:\tlearn: 0.2266655\ttotal: 1.3s\tremaining: 34.8ms\n974:\tlearn: 0.2265102\ttotal: 1.3s\tremaining: 33.5ms\n975:\tlearn: 0.2263874\ttotal: 1.3s\tremaining: 32.1ms\n976:\tlearn: 0.2262242\ttotal: 1.31s\tremaining: 30.8ms\n977:\tlearn: 0.2260340\ttotal: 1.31s\tremaining: 29.4ms\n978:\tlearn: 0.2259051\ttotal: 1.31s\tremaining: 28.1ms\n979:\tlearn: 0.2257953\ttotal: 1.31s\tremaining: 26.8ms\n980:\tlearn: 0.2256369\ttotal: 1.31s\tremaining: 25.4ms\n981:\tlearn: 0.2255181\ttotal: 1.31s\tremaining: 24.1ms\n982:\tlearn: 0.2253744\ttotal: 1.32s\tremaining: 22.8ms\n983:\tlearn: 0.2253042\ttotal: 1.32s\tremaining: 21.4ms\n984:\tlearn: 0.2251955\ttotal: 1.32s\tremaining: 20.1ms\n985:\tlearn: 0.2250286\ttotal: 1.32s\tremaining: 18.8ms\n986:\tlearn: 0.2248336\ttotal: 1.32s\tremaining: 17.4ms\n987:\tlearn: 0.2246963\ttotal: 1.32s\tremaining: 16.1ms\n988:\tlearn: 0.2245518\ttotal: 1.32s\tremaining: 14.7ms\n989:\tlearn: 0.2244328\ttotal: 1.32s\tremaining: 13.4ms\n990:\tlearn: 0.2242437\ttotal: 1.33s\tremaining: 12.1ms\n991:\tlearn: 0.2241087\ttotal: 1.33s\tremaining: 10.7ms\n992:\tlearn: 0.2239619\ttotal: 1.33s\tremaining: 9.37ms\n993:\tlearn: 0.2238540\ttotal: 1.33s\tremaining: 8.03ms\n994:\tlearn: 0.2237682\ttotal: 1.33s\tremaining: 6.7ms\n995:\tlearn: 0.2235843\ttotal: 1.33s\tremaining: 5.36ms\n996:\tlearn: 0.2234413\ttotal: 1.33s\tremaining: 4.02ms\n997:\tlearn: 0.2233262\ttotal: 1.34s\tremaining: 2.68ms\n998:\tlearn: 0.2231933\ttotal: 1.34s\tremaining: 1.34ms\n999:\tlearn: 0.2231028\ttotal: 1.34s\tremaining: 0us\n","output_type":"stream"},{"execution_count":75,"output_type":"execute_result","data":{"text/plain":"StackingClassifier(classifiers=[RandomForestClassifier(), SVC(),\n LogisticRegression(), DecisionTreeClassifier(),\n KNeighborsClassifier(),\n GradientBoostingClassifier(),\n AdaBoostClassifier(),\n ,\n ExtraTreesClassifier(),\n XGBClassifier(base_score=None, booster=None,\n callbacks=None,\n colsample_bylevel=None,\n colsamp...\n interaction_constraints=None,\n learning_rate=None, max_bin=None,\n max_cat_threshold=None,\n max_cat_to_onehot=None,\n max_delta_step=None,\n max_depth=None, max_leaves=None,\n min_child_weight=None,\n missing=nan,\n monotone_constraints=None,\n multi_strategy=None,\n n_estimators=None, n_jobs=None,\n num_parallel_tree=None,\n random_state=None, ...),\n BaggingClassifier()],\n meta_classifier=LogisticRegression())","text/html":"
StackingClassifier(classifiers=[RandomForestClassifier(), SVC(),\n                                LogisticRegression(), DecisionTreeClassifier(),\n                                KNeighborsClassifier(),\n                                GradientBoostingClassifier(),\n                                AdaBoostClassifier(),\n                                <catboost.core.CatBoostClassifier object at 0x7f117f84e860>,\n                                ExtraTreesClassifier(),\n                                XGBClassifier(base_score=None, booster=None,\n                                              callbacks=None,\n                                              colsample_bylevel=None,\n                                              colsamp...\n                                              interaction_constraints=None,\n                                              learning_rate=None, max_bin=None,\n                                              max_cat_threshold=None,\n                                              max_cat_to_onehot=None,\n                                              max_delta_step=None,\n                                              max_depth=None, max_leaves=None,\n                                              min_child_weight=None,\n                                              missing=nan,\n                                              monotone_constraints=None,\n                                              multi_strategy=None,\n                                              n_estimators=None, n_jobs=None,\n                                              num_parallel_tree=None,\n                                              random_state=None, ...),\n                                BaggingClassifier()],\n                   meta_classifier=LogisticRegression())
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"},"metadata":{}}]},{"cell_type":"code","source":"# Predict with Stacking Classifier\ny_pred_stack = stack.predict(X_test)\n# Calculate evaluation metrics for Stacking Classifier\naccuracy_stack = accuracy_score(y_test, y_pred_stack)\nreport_stack = classification_report(y_test, y_pred_stack, output_dict=True)\nprecision_stack = report_stack['macro avg']['precision']\nrecall_stack = report_stack['macro avg']['recall']\nf1_score_stack = report_stack['macro avg']['f1-score']\n","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:16.130305Z","iopub.execute_input":"2024-07-21T17:50:16.130900Z","iopub.status.idle":"2024-07-21T17:50:16.287702Z","shell.execute_reply.started":"2024-07-21T17:50:16.130855Z","shell.execute_reply":"2024-07-21T17:50:16.286197Z"},"trusted":true},"execution_count":76,"outputs":[]},{"cell_type":"code","source":"# Append Stacking Classifier results to the evaluation results\nevaluation_results.append({\n 'Model': 'Stacking Classifier',\n 'Accuracy': accuracy_stack,\n 'Precision': precision_stack,\n 'Recall': recall_stack,\n 'F1 Score': f1_score_stack\n})\n# Update results DataFrame\nresults = pd.DataFrame(evaluation_results)\n# Save updated results to CSV\nresults.to_csv('evaluation_results_with_stacking.csv', index=False)\n# Display updated evaluation results in table form\nprint(results)","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:16.289712Z","iopub.execute_input":"2024-07-21T17:50:16.290061Z","iopub.status.idle":"2024-07-21T17:50:16.305693Z","shell.execute_reply.started":"2024-07-21T17:50:16.290034Z","shell.execute_reply":"2024-07-21T17:50:16.304298Z"},"trusted":true},"execution_count":77,"outputs":[{"name":"stdout","text":" Model Accuracy Precision Recall F1 Score\n0 Random Forest 0.752665 0.686394 0.660551 0.669750\n1 Support Vector Classifier 0.773987 0.721856 0.665816 0.681222\n2 Logistic Regression 0.763326 0.702406 0.663184 0.675493\n3 Decision Tree 0.695096 0.620161 0.620728 0.620441\n4 K-Nearest Neighbors 0.735608 0.661683 0.639267 0.646975\n5 Gradient Boosting 0.773987 0.717072 0.689528 0.699925\n6 AdaBoost 0.782516 0.728192 0.712026 0.718984\n7 CatBoost 0.761194 0.699333 0.683050 0.689800\n8 Extra Trees 0.761194 0.699206 0.659337 0.671569\n9 XGBoost 0.727079 0.656931 0.652337 0.654464\n10 Bagging Classifier 0.733475 0.657757 0.633050 0.641036\n11 Stacking Classifier 0.750533 0.683425 0.659076 0.667849\n","output_type":"stream"}]},{"cell_type":"code","source":"# Display confusion matrix for Stacking Classifier\ncm_stack = confusion_matrix(y_test, y_pred_stack)\ndisp_stack = ConfusionMatrixDisplay(confusion_matrix=cm_stack)\ndisp_stack.plot()\nplt.title(\"Confusion Matrix for Stacking Classifier\")\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:16.307376Z","iopub.execute_input":"2024-07-21T17:50:16.307804Z","iopub.status.idle":"2024-07-21T17:50:16.579260Z","shell.execute_reply.started":"2024-07-21T17:50:16.307769Z","shell.execute_reply":"2024-07-21T17:50:16.578006Z"},"trusted":true},"execution_count":78,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# Plot accuracies\nplt.figure(figsize=(12, 8))\nplt.bar(results['Model'], results['Accuracy'], color='skyblue')\nplt.xlabel('Model')\nplt.ylabel('Accuracy')\nplt.title('Model Accuracies')\nplt.xticks(rotation=45)\nplt.ylim(0, 1)\nfor i in range(len(results)):\n plt.text(i, results['Accuracy'][i] + 0.01, f\"{results['Accuracy'][i]:.2f}\", ha='center')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-07-21T17:50:16.580592Z","iopub.execute_input":"2024-07-21T17:50:16.580923Z","iopub.status.idle":"2024-07-21T17:50:16.914839Z","shell.execute_reply.started":"2024-07-21T17:50:16.580894Z","shell.execute_reply":"2024-07-21T17:50:16.913614Z"},"trusted":true},"execution_count":79,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]} \ No newline at end of file diff --git a/Fictional Character Battle Outcome Prediction/README.md b/Fictional Character Battle Outcome Prediction/README.md new file mode 100644 index 000000000..adf3bbfea --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/README.md @@ -0,0 +1,119 @@ +# Fictional Character Battle Outcome Prediction Project + +## Goal +The goal of this project is to predict the outcomes of battles between fictional characters using various machine learning models. + +## Dataset +The dataset used for this project is the ["Fictional Character Battle Outcome Prediction"](https://www.kaggle.com/datasets/rabieelkharoua/fictional-character-battle-outcome-prediction/data) dataset from Kaggle. + +## Description +The dataset contains features related to fictional characters and the outcomes of their battles. The features include attributes such as strength, intelligence, speed, durability, power, and combat skills of the characters. The target variable is the outcome of the battle. + +## What I Had Done +1. **Data Preprocessing**: + - Loaded the dataset. + - Handled missing values. + - Encoded categorical variables. + - Split the data into training and testing sets. + +2. **Exploratory Data Analysis (EDA)**: + - Visualized the distribution of features. + - Analyzed the correlation between features. + - Examined the class distribution of the target variable. + +3. **Model Training and Evaluation**: + - Trained multiple machine learning models. + - Evaluated the performance of each model using accuracy, precision, recall, and F1 score. + - Implemented a stacking classifier as an ensemble method. + +## Models Implemented +The following machine learning models were implemented and evaluated in this project: + +1. **Random Forest**: + - A versatile ensemble learning method that operates by constructing multiple decision trees during training and outputs the mode of the classes for classification. + +2. **Support Vector Classifier (SVC)**: + - A supervised learning model that analyzes data for classification by finding the hyperplane that best separates the classes. + +3. **Logistic Regression**: + - A statistical model that in its basic form uses a logistic function to model a binary dependent variable. + +4. **Decision Tree**: + - A decision support tool that uses a tree-like graph of decisions and their possible consequences. + +5. **K-Nearest Neighbors (KNN)**: + - A simple, instance-based learning algorithm that assigns a class to a sample based on the majority class among its k-nearest neighbors. + +6. **Gradient Boosting**: + - An ensemble technique that builds models sequentially, each new model correcting errors made by previous models. + +7. **AdaBoost**: + - A boosting algorithm that combines the predictions of several base estimators to improve robustness over a single estimator. + +8. **CatBoost**: + - A high-performance library for gradient boosting on decision trees, especially well-suited for categorical data. + +9. **Extra Trees**: + - An ensemble learning method similar to Random Forest but with more randomness in the splitting of nodes. + +10. **XGBoost**: + - An optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. + +11. **Bagging Classifier**: + - An ensemble meta-estimator that fits base classifiers each on random subsets of the original dataset and then aggregates their predictions. + +12. **Stacking Classifier**: + - An ensemble learning technique that combines multiple base classifiers via a meta-classifier. The base classifiers are trained on the training dataset, and the meta-classifier is trained on the outputs of the base classifiers. + +## Libraries Needed +The following libraries were used in this project: +- pandas +- numpy +- matplotlib +- scikit-learn +- xgboost +- catboost +- mlxtend + +## EDA Results +- Visualizations of feature distributions showed that most features are normally distributed. +- Correlation analysis indicated that certain features like strength and power have a high correlation. +- The target variable was found to be balanced, with a nearly equal distribution of battle outcomes. + +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___13_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___14_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___15_1.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___15_3.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___15_5.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___16_1.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___17_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___18_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___19_0.png?raw=true) +![eda-1](https://github.com/adi271001/ML-Crate/blob/Fictional-Character-Battle/Fictional%20Character%20Battle%20Outcome%20Prediction/Images/__results___20_0.png?raw=true) + +## Performance of the Models based on Accuracy Scores + +| Model | Accuracy | Precision | Recall | F1 Score | +|-------------------------|----------|-----------|--------|----------| +| Random Forest | 0.752665 | 0.686600 | 0.662923 | 0.671616 | +| Support Vector Classifier | 0.773987 | 0.721856 | 0.665816 | 0.681222 | +| Logistic Regression | 0.763326 | 0.702406 | 0.663184 | 0.675493 | +| Decision Tree | 0.710021 | 0.638167 | 0.638167 | 0.638167 | +| K-Nearest Neighbors | 0.735608 | 0.661683 | 0.639267 | 0.646975 | +| Gradient Boosting | 0.773987 | 0.717072 | 0.689528 | 0.699925 | +| AdaBoost | 0.782516 | 0.728192 | 0.712026 | 0.718984 | +| CatBoost | 0.761194 | 0.699333 | 0.683050 | 0.689800 | +| Extra Trees | 0.733475 | 0.658311 | 0.635421 | 0.643107 | +| XGBoost | 0.727079 | 0.656931 | 0.652337 | 0.654464 | +| Bagging Classifier | 0.739872 | 0.667861 | 0.644588 | 0.652669 | +| Stacking Classifier | 0.752665 | 0.687412 | 0.670036 | 0.676997 | + +## Conclusion +Among the models evaluated, **AdaBoost** achieved the highest accuracy of 78.25%. This model is the best performer due to its ability to adaptively adjust the weights of misclassified instances, leading to improved performance in the prediction task. AdaBoost’s strong performance across multiple metrics, including precision, recall, and F1 score, highlights its effectiveness in handling this classification problem. + +## Signature +- **Name:** Aditya D +- **Github:** [https://www.github.com/adi271001](https://www.github.com/adi271001) +- **LinkedIn:** [https://www.linkedin.com/in/aditya-d-23453a179/](https://www.linkedin.com/in/aditya-d-23453a179/) +- **Topmate:** [https://topmate.io/aditya_d/](https://topmate.io/aditya_d/) +- **Twitter:** [https://x.com/ADITYAD29257528](https://x.com/ADITYAD29257528) diff --git a/Fictional Character Battle Outcome Prediction/Results/evaluation_results.csv b/Fictional Character Battle Outcome Prediction/Results/evaluation_results.csv new file mode 100644 index 000000000..10e7c863a --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/Results/evaluation_results.csv @@ -0,0 +1,12 @@ +Model,Accuracy,Precision,Recall,F1 Score +Random Forest,0.7377398720682303,0.6640658631080499,0.6383707737690039,0.6467789636106468 +Support Vector Classifier,0.7739872068230277,0.7218562147064181,0.6658157476741547,0.6812224274135632 +Logistic Regression,0.7633262260127932,0.7024064171122995,0.6631835715906512,0.6754932211313699 +Decision Tree,0.7142857142857143,0.6414804016844833,0.6387451781257091,0.6400407807917888 +K-Nearest Neighbors,0.7356076759061834,0.6616833508956796,0.639267075107783,0.6469745532245532 +Gradient Boosting,0.7739872068230277,0.7170720931441343,0.68952802359882,0.6999251533149837 +AdaBoost,0.7825159914712153,0.7281918530819576,0.712026321760835,0.7189835048639504 +CatBoost,0.7611940298507462,0.6993328391401038,0.6830496936691627,0.6898001606273917 +Extra Trees,0.7505330490405118,0.6828282828282828,0.6519627864760609,0.6620309064368906 +XGBoost,0.7270788912579957,0.6569308087891539,0.6523371908327661,0.6544642446010038 +Bagging Classifier,0.7526652452025586,0.6860840108401084,0.6558089403222147,0.6659051830017195 diff --git a/Fictional Character Battle Outcome Prediction/Results/evaluation_results_with_stacking.csv b/Fictional Character Battle Outcome Prediction/Results/evaluation_results_with_stacking.csv new file mode 100644 index 000000000..c7e3c951a --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/Results/evaluation_results_with_stacking.csv @@ -0,0 +1,13 @@ +Model,Accuracy,Precision,Recall,F1 Score +Random Forest,0.7377398720682303,0.6640658631080499,0.6383707737690039,0.6467789636106468 +Support Vector Classifier,0.7739872068230277,0.7218562147064181,0.6658157476741547,0.6812224274135632 +Logistic Regression,0.7633262260127932,0.7024064171122995,0.6631835715906512,0.6754932211313699 +Decision Tree,0.7142857142857143,0.6414804016844833,0.6387451781257091,0.6400407807917888 +K-Nearest Neighbors,0.7356076759061834,0.6616833508956796,0.639267075107783,0.6469745532245532 +Gradient Boosting,0.7739872068230277,0.7170720931441343,0.68952802359882,0.6999251533149837 +AdaBoost,0.7825159914712153,0.7281918530819576,0.712026321760835,0.7189835048639504 +CatBoost,0.7611940298507462,0.6993328391401038,0.6830496936691627,0.6898001606273917 +Extra Trees,0.7505330490405118,0.6828282828282828,0.6519627864760609,0.6620309064368906 +XGBoost,0.7270788912579957,0.6569308087891539,0.6523371908327661,0.6544642446010038 +Bagging Classifier,0.7526652452025586,0.6860840108401084,0.6558089403222147,0.6659051830017195 +Stacking Classifier,0.7569296375266524,0.6924390243902439,0.6611300204220558,0.671665438467207 diff --git a/Fictional Character Battle Outcome Prediction/requirements.txt b/Fictional Character Battle Outcome Prediction/requirements.txt new file mode 100644 index 000000000..011eb943d --- /dev/null +++ b/Fictional Character Battle Outcome Prediction/requirements.txt @@ -0,0 +1,9 @@ +pandas==2.0.3 +numpy==1.24.3 +seaborn==0.11.2 +matplotlib==3.7.1 +scikit-learn==1.2.2 +scipy==1.10.1 +xgboost==1.7.6 +catboost==1.2 +mlxtend==0.22.0