final_output.txt

C:\Users\taxborn\PycharmProjects\mauthPart2\venv\Scripts\python.exe C:\Users\taxborn\PycharmProjects\mauthPart2\main.py

mAuth Models Run.
Current parameters:
Train/Test split: 70.0/30.0
Random state constant for reproducibility: 0
Feature file used: ./data/user_all_features_SQ128.csv
[Sequencing] length used: 128
[Anomaly detection] Percentage of negative (imposter) data: 50.0%
Starting processing for subject 0
> features selected:
Index(['ID', 'mean_x_speed', 'mean_y_speed', 'mean_speed', 'mean_x_acc',
       'mean_y_acc', 'mean_acc', 'mean_jerk', 'mean_ang', 'mean_curve',
       'mean_tan', 'std_x_speed', 'std_y_speed', 'std_speed', 'std_x_acc',
       'std_y_acc', 'std_acc', 'std_ang', 'std_jerk', 'std_curve', 'std_tan',
       'min_tan', 'min_x_speed', 'min_y_speed', 'min_speed', 'min_x_acc',
       'min_y_acc', 'min_acc', 'min_ang', 'min_jerk', 'min_curve',
       'max_x_speed', 'max_y_speed', 'max_speed', 'max_x_acc', 'max_y_acc',
       'max_acc', 'max_ang', 'max_jerk', 'max_curve', 'max_tan', 'traj_length',
       'numCritPoints', 'mean_speed_over_dist', 'std_speed_over_dist',
       'min_speed_over_dist', 'max_speed_over_dist',
       'mean_acceleration_over_dist', 'std_acceleration_over_dist',
       'max_acceleration_over_dist', 'min_acceleration_over_dist',
       'mean_smoothness', 'std_smoothness', 'min_smoothness', 'max_smoothness',
       'area_under_curve'],
      dtype='object')
------------------- Starting KNN --------------------
number of events: 103373, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 12.689s
> KNN Can process 3491.565 events / second

k-Nearest Neighbors subject 0 Validation details:
Accuracy: 0.972, Precision: 0.963, Recall: 0.982, F1: 0.972
[[21460   834]
 [  398 21611]]
FAR : 0.038 FRR: 0.018 ERR: 0.028
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     22294
         1.0       0.96      0.98      0.97     22009

    accuracy                           0.97     44303
   macro avg       0.97      0.97      0.97     44303
weighted avg       0.97      0.97      0.97     44303

----- Finished k-Nearest Neighbors on subject 0 -----
Starting processing for subject 1
------------------- Starting KNN --------------------
number of events: 109258, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 14.484s
> KNN Can process 3232.964 events / second

k-Nearest Neighbors subject 1 Validation details:
Accuracy: 0.979, Precision: 0.968, Recall: 0.989, F1: 0.979
[[22856   760]
 [  245 22965]]
FAR : 0.033 FRR: 0.01 ERR: 0.022
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.97      0.98     23616
         1.0       0.97      0.99      0.98     23210

    accuracy                           0.98     46826
   macro avg       0.98      0.98      0.98     46826
weighted avg       0.98      0.98      0.98     46826

----- Finished k-Nearest Neighbors on subject 1 -----
Starting processing for subject 2
------------------- Starting KNN --------------------
number of events: 86220, k = 3
> KNN Fit time: 0.008s
> KNN Predict time: 9.315s
> KNN Can process 3967.06 events / second

k-Nearest Neighbors subject 2 Validation details:
Accuracy: 0.975, Precision: 0.97, Recall: 0.981, F1: 0.975
[[17953   567]
 [  356 18076]]
FAR : 0.031 FRR: 0.019 ERR: 0.025
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.97     18520
         1.0       0.97      0.98      0.98     18432

    accuracy                           0.98     36952
   macro avg       0.98      0.98      0.98     36952
weighted avg       0.98      0.98      0.98     36952

----- Finished k-Nearest Neighbors on subject 2 -----
Starting processing for subject 3
------------------- Starting KNN --------------------
number of events: 95975, k = 3
> KNN Fit time: 0.008s
> KNN Predict time: 11.531s
> KNN Can process 3567.023 events / second

k-Nearest Neighbors subject 3 Validation details:
Accuracy: 0.978, Precision: 0.969, Recall: 0.988, F1: 0.978
[[20076   637]
 [  252 20168]]
FAR : 0.031 FRR: 0.012 ERR: 0.022
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.97      0.98     20713
         1.0       0.97      0.99      0.98     20420

    accuracy                           0.98     41133
   macro avg       0.98      0.98      0.98     41133
weighted avg       0.98      0.98      0.98     41133

----- Finished k-Nearest Neighbors on subject 3 -----
Starting processing for subject 4
------------------- Starting KNN --------------------
number of events: 91096, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 10.597s
> KNN Can process 3684.136 events / second

k-Nearest Neighbors subject 4 Validation details:
Accuracy: 0.97, Precision: 0.956, Recall: 0.986, F1: 0.971
[[18723   888]
 [  273 19158]]
FAR : 0.047 FRR: 0.014 ERR: 0.03
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.95      0.97     19611
         1.0       0.96      0.99      0.97     19431

    accuracy                           0.97     39042
   macro avg       0.97      0.97      0.97     39042
weighted avg       0.97      0.97      0.97     39042

----- Finished k-Nearest Neighbors on subject 4 -----
Starting processing for subject 5
------------------- Starting KNN --------------------
number of events: 148985, k = 3
> KNN Fit time: 0.012s
> KNN Predict time: 28.254s
> KNN Can process 2259.876 events / second

k-Nearest Neighbors subject 5 Validation details:
Accuracy: 0.98, Precision: 0.97, Recall: 0.99, F1: 0.98
[[31014   988]
 [  307 31542]]
FAR : 0.032 FRR: 0.009 ERR: 0.02
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.97      0.98     32002
         1.0       0.97      0.99      0.98     31849

    accuracy                           0.98     63851
   macro avg       0.98      0.98      0.98     63851
weighted avg       0.98      0.98      0.98     63851

----- Finished k-Nearest Neighbors on subject 5 -----
Starting processing for subject 6
------------------- Starting KNN --------------------
number of events: 106318, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 14.638s
> KNN Can process 3112.81 events / second

k-Nearest Neighbors subject 6 Validation details:
Accuracy: 0.972, Precision: 0.963, Recall: 0.981, F1: 0.972
[[22160   853]
 [  426 22127]]
FAR : 0.038 FRR: 0.019 ERR: 0.028
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     23013
         1.0       0.96      0.98      0.97     22553

    accuracy                           0.97     45566
   macro avg       0.97      0.97      0.97     45566
weighted avg       0.97      0.97      0.97     45566

----- Finished k-Nearest Neighbors on subject 6 -----
Starting processing for subject 7
------------------- Starting KNN --------------------
number of events: 74865, k = 3
> KNN Fit time: 0.006s
> KNN Predict time: 7.142s
> KNN Can process 4492.311 events / second

k-Nearest Neighbors subject 7 Validation details:
Accuracy: 0.966, Precision: 0.945, Recall: 0.988, F1: 0.966
[[15266   907]
 [  192 15720]]
FAR : 0.059 FRR: 0.012 ERR: 0.036
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.94      0.97     16173
         1.0       0.95      0.99      0.97     15912

    accuracy                           0.97     32085
   macro avg       0.97      0.97      0.97     32085
weighted avg       0.97      0.97      0.97     32085

----- Finished k-Nearest Neighbors on subject 7 -----
Starting processing for subject 8
------------------- Starting KNN --------------------
number of events: 114891, k = 3
> KNN Fit time: 0.009s
> KNN Predict time: 16.756s
> KNN Can process 2938.583 events / second

k-Nearest Neighbors subject 8 Validation details:
Accuracy: 0.978, Precision: 0.969, Recall: 0.988, F1: 0.978
[[24044   773]
 [  305 24117]]
FAR : 0.032 FRR: 0.012 ERR: 0.022
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.97      0.98     24817
         1.0       0.97      0.99      0.98     24422

    accuracy                           0.98     49239
   macro avg       0.98      0.98      0.98     49239
weighted avg       0.98      0.98      0.98     49239

----- Finished k-Nearest Neighbors on subject 8 -----
Starting processing for subject 9
------------------- Starting KNN --------------------
number of events: 105872, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 14.249s
> KNN Can process 3184.286 events / second

k-Nearest Neighbors subject 9 Validation details:
Accuracy: 0.975, Precision: 0.962, Recall: 0.989, F1: 0.975
[[22016   869]
 [  250 22239]]
FAR : 0.039 FRR: 0.011 ERR: 0.025
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.96      0.98     22885
         1.0       0.96      0.99      0.98     22489

    accuracy                           0.98     45374
   macro avg       0.98      0.98      0.98     45374
weighted avg       0.98      0.98      0.98     45374

----- Finished k-Nearest Neighbors on subject 9 -----
Starting processing for subject 10
------------------- Starting KNN --------------------
number of events: 108200, k = 3
> KNN Fit time: 0.008s
> KNN Predict time: 14.822s
> KNN Can process 3128.632 events / second

k-Nearest Neighbors subject 10 Validation details:
Accuracy: 0.974, Precision: 0.968, Recall: 0.981, F1: 0.974
[[22726   747]
 [  436 22463]]
FAR : 0.032 FRR: 0.019 ERR: 0.026
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.97     23473
         1.0       0.97      0.98      0.97     22899

    accuracy                           0.97     46372
   macro avg       0.97      0.97      0.97     46372
weighted avg       0.97      0.97      0.97     46372

---- Finished k-Nearest Neighbors on subject 10 -----
Starting processing for subject 11
------------------- Starting KNN --------------------
number of events: 111745, k = 3
> KNN Fit time: 0.011s
> KNN Predict time: 16.338s
> KNN Can process 2931.183 events / second

k-Nearest Neighbors subject 11 Validation details:
Accuracy: 0.978, Precision: 0.967, Recall: 0.99, F1: 0.978
[[23350   802]
 [  234 23505]]
FAR : 0.034 FRR: 0.01 ERR: 0.022
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.97      0.98     24152
         1.0       0.97      0.99      0.98     23739

    accuracy                           0.98     47891
   macro avg       0.98      0.98      0.98     47891
weighted avg       0.98      0.98      0.98     47891

---- Finished k-Nearest Neighbors on subject 11 -----
Starting processing for subject 12
------------------- Starting KNN --------------------
number of events: 108476, k = 3
> KNN Fit time: 0.01s
> KNN Predict time: 15.013s
> KNN Can process 3096.619 events / second

k-Nearest Neighbors subject 12 Validation details:
Accuracy: 0.976, Precision: 0.962, Recall: 0.991, F1: 0.976
[[22597   909]
 [  197 22787]]
FAR : 0.04 FRR: 0.008 ERR: 0.024
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.96      0.98     23506
         1.0       0.96      0.99      0.98     22984

    accuracy                           0.98     46490
   macro avg       0.98      0.98      0.98     46490
weighted avg       0.98      0.98      0.98     46490

---- Finished k-Nearest Neighbors on subject 12 -----
Starting processing for subject 13
------------------- Starting KNN --------------------
number of events: 82296, k = 3
> KNN Fit time: 0.007s
> KNN Predict time: 8.61s
> KNN Can process 4096.409 events / second

k-Nearest Neighbors subject 13 Validation details:
Accuracy: 0.973, Precision: 0.964, Recall: 0.983, F1: 0.973
[[16998   647]
 [  305 17320]]
FAR : 0.037 FRR: 0.017 ERR: 0.027
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     17645
         1.0       0.96      0.98      0.97     17625

    accuracy                           0.97     35270
   macro avg       0.97      0.97      0.97     35270
weighted avg       0.97      0.97      0.97     35270

---- Finished k-Nearest Neighbors on subject 13 -----
Starting processing for subject 14
------------------- Starting KNN --------------------
number of events: 119931, k = 3
> KNN Fit time: 0.012s
> KNN Predict time: 18.051s
> KNN Can process 2847.421 events / second

k-Nearest Neighbors subject 14 Validation details:
Accuracy: 0.977, Precision: 0.971, Recall: 0.984, F1: 0.977
[[25175   750]
 [  418 25056]]
FAR : 0.029 FRR: 0.016 ERR: 0.022
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.98     25925
         1.0       0.97      0.98      0.98     25474

    accuracy                           0.98     51399
   macro avg       0.98      0.98      0.98     51399
weighted avg       0.98      0.98      0.98     51399

---- Finished k-Nearest Neighbors on subject 14 -----
Starting processing for subject 0
> features selected:
Index(['ID', 'mean_x_speed', 'mean_y_speed', 'mean_speed', 'mean_x_acc',
       'mean_y_acc', 'mean_acc', 'mean_jerk', 'mean_ang', 'mean_curve',
       'mean_tan', 'std_x_speed', 'std_y_speed', 'std_speed', 'std_x_acc',
       'std_y_acc', 'std_acc', 'std_ang', 'std_jerk', 'std_curve', 'std_tan',
       'min_tan', 'min_x_speed', 'min_y_speed', 'min_speed', 'min_x_acc',
       'min_y_acc', 'min_acc', 'min_ang', 'min_jerk', 'min_curve',
       'max_x_speed', 'max_y_speed', 'max_speed', 'max_x_acc', 'max_y_acc',
       'max_acc', 'max_ang', 'max_jerk', 'max_curve', 'max_tan', 'traj_length',
       'numCritPoints', 'mean_speed_over_dist', 'std_speed_over_dist',
       'min_speed_over_dist', 'max_speed_over_dist',
       'mean_acceleration_over_dist', 'std_acceleration_over_dist',
       'max_acceleration_over_dist', 'min_acceleration_over_dist',
       'mean_smoothness', 'std_smoothness', 'min_smoothness', 'max_smoothness',
       'area_under_curve'],
      dtype='object')
-------------------- Starting DT --------------------
> Decision Tree Fit time: 6.396s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4647132.749 events / second

Decision Tree subject 0 Validation details:
Accuracy: 0.965, Precision: 0.956, Recall: 0.974, F1: 0.965
[[21312   982]
 [  563 21446]]
FAR : 0.045 FRR: 0.025 ERR: 0.035
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.96      0.97     22294
         1.0       0.96      0.97      0.97     22009

    accuracy                           0.97     44303
   macro avg       0.97      0.97      0.97     44303
weighted avg       0.97      0.97      0.97     44303

-------- Finished Decision Tree on subject 0 --------
Starting processing for subject 1
-------------------- Starting DT --------------------
> Decision Tree Fit time: 6.086s
> Decision Tree Predict time: 0.009s
> Decision Tree Can process 5182670.443 events / second

Decision Tree subject 1 Validation details:
Accuracy: 0.962, Precision: 0.951, Recall: 0.974, F1: 0.962
[[22461  1155]
 [  613 22597]]
FAR : 0.05 FRR: 0.026 ERR: 0.038
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.95      0.96     23616
         1.0       0.95      0.97      0.96     23210

    accuracy                           0.96     46826
   macro avg       0.96      0.96      0.96     46826
weighted avg       0.96      0.96      0.96     46826

-------- Finished Decision Tree on subject 1 --------
Starting processing for subject 2
-------------------- Starting DT --------------------
> Decision Tree Fit time: 5.81s
> Decision Tree Predict time: 0.008s
> Decision Tree Can process 4584763.242 events / second

Decision Tree subject 2 Validation details:
Accuracy: 0.973, Precision: 0.967, Recall: 0.98, F1: 0.973
[[17897   623]
 [  362 18070]]
FAR : 0.034 FRR: 0.019 ERR: 0.027
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.97     18520
         1.0       0.97      0.98      0.97     18432

    accuracy                           0.97     36952
   macro avg       0.97      0.97      0.97     36952
weighted avg       0.97      0.97      0.97     36952

-------- Finished Decision Tree on subject 2 --------
Starting processing for subject 3
-------------------- Starting DT --------------------
> Decision Tree Fit time: 6.689s
> Decision Tree Predict time: 0.008s
> Decision Tree Can process 4919567.322 events / second

Decision Tree subject 3 Validation details:
Accuracy: 0.966, Precision: 0.957, Recall: 0.975, F1: 0.966
[[19828   885]
 [  508 19912]]
FAR : 0.044 FRR: 0.024 ERR: 0.034
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     20713
         1.0       0.96      0.98      0.97     20420

    accuracy                           0.97     41133
   macro avg       0.97      0.97      0.97     41133
weighted avg       0.97      0.97      0.97     41133

-------- Finished Decision Tree on subject 3 --------
Starting processing for subject 4
-------------------- Starting DT --------------------
> Decision Tree Fit time: 5.24s
> Decision Tree Predict time: 0.008s
> Decision Tree Can process 4743743.244 events / second

Decision Tree subject 4 Validation details:
Accuracy: 0.952, Precision: 0.938, Recall: 0.968, F1: 0.953
[[18362  1249]
 [  625 18806]]
FAR : 0.066 FRR: 0.031 ERR: 0.048
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.94      0.95     19611
         1.0       0.94      0.97      0.95     19431

    accuracy                           0.95     39042
   macro avg       0.95      0.95      0.95     39042
weighted avg       0.95      0.95      0.95     39042

-------- Finished Decision Tree on subject 4 --------
Starting processing for subject 5
-------------------- Starting DT --------------------
> Decision Tree Fit time: 11.036s
> Decision Tree Predict time: 0.014s
> Decision Tree Can process 4563059.152 events / second

Decision Tree subject 5 Validation details:
Accuracy: 0.974, Precision: 0.966, Recall: 0.982, F1: 0.974
[[30913  1089]
 [  560 31289]]
FAR : 0.035 FRR: 0.017 ERR: 0.026
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.97     32002
         1.0       0.97      0.98      0.97     31849

    accuracy                           0.97     63851
   macro avg       0.97      0.97      0.97     63851
weighted avg       0.97      0.97      0.97     63851

-------- Finished Decision Tree on subject 5 --------
Starting processing for subject 6
-------------------- Starting DT --------------------
> Decision Tree Fit time: 6.131s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4547713.41 events / second

Decision Tree subject 6 Validation details:
Accuracy: 0.972, Precision: 0.964, Recall: 0.979, F1: 0.972
[[22186   827]
 [  464 22089]]
FAR : 0.037 FRR: 0.02 ERR: 0.028
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     23013
         1.0       0.96      0.98      0.97     22553

    accuracy                           0.97     45566
   macro avg       0.97      0.97      0.97     45566
weighted avg       0.97      0.97      0.97     45566

-------- Finished Decision Tree on subject 6 --------
Starting processing for subject 7
-------------------- Starting DT --------------------
> Decision Tree Fit time: 4.77s
> Decision Tree Predict time: 0.006s
> Decision Tree Can process 5345338.57 events / second

Decision Tree subject 7 Validation details:
Accuracy: 0.956, Precision: 0.941, Recall: 0.971, F1: 0.956
[[15209   964]
 [  454 15458]]
FAR : 0.062 FRR: 0.028 ERR: 0.045
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.94      0.96     16173
         1.0       0.94      0.97      0.96     15912

    accuracy                           0.96     32085
   macro avg       0.96      0.96      0.96     32085
weighted avg       0.96      0.96      0.96     32085

-------- Finished Decision Tree on subject 7 --------
Starting processing for subject 8
-------------------- Starting DT --------------------
> Decision Tree Fit time: 7.088s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4927429.071 events / second

Decision Tree subject 8 Validation details:
Accuracy: 0.972, Precision: 0.963, Recall: 0.981, F1: 0.972
[[23905   912]
 [  455 23967]]
FAR : 0.037 FRR: 0.018 ERR: 0.027
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     24817
         1.0       0.96      0.98      0.97     24422

    accuracy                           0.97     49239
   macro avg       0.97      0.97      0.97     49239
weighted avg       0.97      0.97      0.97     49239

-------- Finished Decision Tree on subject 8 --------
Starting processing for subject 9
-------------------- Starting DT --------------------
> Decision Tree Fit time: 7.021s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4537404.327 events / second

Decision Tree subject 9 Validation details:
Accuracy: 0.958, Precision: 0.943, Recall: 0.974, F1: 0.958
[[21560  1325]
 [  591 21898]]
FAR : 0.06 FRR: 0.025 ERR: 0.042
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.94      0.96     22885
         1.0       0.94      0.97      0.96     22489

    accuracy                           0.96     45374
   macro avg       0.96      0.96      0.96     45374
weighted avg       0.96      0.96      0.96     45374

-------- Finished Decision Tree on subject 9 --------
Starting processing for subject 10
-------------------- Starting DT --------------------
> Decision Tree Fit time: 7.798s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4636872.767 events / second

Decision Tree subject 10 Validation details:
Accuracy: 0.969, Precision: 0.96, Recall: 0.978, F1: 0.969
[[22539   934]
 [  505 22394]]
FAR : 0.041 FRR: 0.022 ERR: 0.032
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     23473
         1.0       0.96      0.98      0.97     22899

    accuracy                           0.97     46372
   macro avg       0.97      0.97      0.97     46372
weighted avg       0.97      0.97      0.97     46372

------- Finished Decision Tree on subject 10 --------
Starting processing for subject 11
-------------------- Starting DT --------------------
> Decision Tree Fit time: 7.358s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4704973.013 events / second

Decision Tree subject 11 Validation details:
Accuracy: 0.961, Precision: 0.949, Recall: 0.975, F1: 0.962
[[22897  1255]
 [  590 23149]]
FAR : 0.053 FRR: 0.024 ERR: 0.038
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.95      0.96     24152
         1.0       0.95      0.98      0.96     23739

    accuracy                           0.96     47891
   macro avg       0.96      0.96      0.96     47891
weighted avg       0.96      0.96      0.96     47891

------- Finished Decision Tree on subject 11 --------
Starting processing for subject 12
-------------------- Starting DT --------------------
> Decision Tree Fit time: 7.285s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 4645349.556 events / second

Decision Tree subject 12 Validation details:
Accuracy: 0.967, Precision: 0.956, Recall: 0.979, F1: 0.967
[[22471  1035]
 [  481 22503]]
FAR : 0.045 FRR: 0.02 ERR: 0.032
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     23506
         1.0       0.96      0.98      0.97     22984

    accuracy                           0.97     46490
   macro avg       0.97      0.97      0.97     46490
weighted avg       0.97      0.97      0.97     46490

------- Finished Decision Tree on subject 12 --------
Starting processing for subject 13
-------------------- Starting DT --------------------
> Decision Tree Fit time: 5.133s
> Decision Tree Predict time: 0.008s
> Decision Tree Can process 4402377.826 events / second

Decision Tree subject 13 Validation details:
Accuracy: 0.974, Precision: 0.969, Recall: 0.98, F1: 0.975
[[17095   550]
 [  350 17275]]
FAR : 0.032 FRR: 0.02 ERR: 0.026
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.97      0.97     17645
         1.0       0.97      0.98      0.97     17625

    accuracy                           0.97     35270
   macro avg       0.97      0.97      0.97     35270
weighted avg       0.97      0.97      0.97     35270

------- Finished Decision Tree on subject 13 --------
Starting processing for subject 14
-------------------- Starting DT --------------------
> Decision Tree Fit time: 8.463s
> Decision Tree Predict time: 0.01s
> Decision Tree Can process 5139904.902 events / second

Decision Tree subject 14 Validation details:
Accuracy: 0.971, Precision: 0.964, Recall: 0.979, F1: 0.971
[[25003   922]
 [  545 24929]]
FAR : 0.036 FRR: 0.021 ERR: 0.028
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.96      0.97     25925
         1.0       0.96      0.98      0.97     25474

    accuracy                           0.97     51399
   macro avg       0.97      0.97      0.97     51399
weighted avg       0.97      0.97      0.97     51399

------- Finished Decision Tree on subject 14 --------
Starting processing for subject 1
Starting processing for subject 4
Starting processing for subject 0
> features selected:
Index(['ID', 'mean_x_speed', 'mean_y_speed', 'mean_speed', 'mean_x_acc',
       'mean_y_acc', 'mean_acc', 'mean_jerk', 'mean_ang', 'mean_curve',
       'mean_tan', 'std_x_speed', 'std_y_speed', 'std_speed', 'std_x_acc',
       'std_y_acc', 'std_acc', 'std_ang', 'std_jerk', 'std_curve', 'std_tan',
       'min_tan', 'min_x_speed', 'min_y_speed', 'min_speed', 'min_x_acc',
       'min_y_acc', 'min_acc', 'min_ang', 'min_jerk', 'min_curve',
       'max_x_speed', 'max_y_speed', 'max_speed', 'max_x_acc', 'max_y_acc',
       'max_acc', 'max_ang', 'max_jerk', 'max_curve', 'max_tan', 'traj_length',
       'numCritPoints', 'mean_speed_over_dist', 'std_speed_over_dist',
       'min_speed_over_dist', 'max_speed_over_dist',
       'mean_acceleration_over_dist', 'std_acceleration_over_dist',
       'max_acceleration_over_dist', 'min_acceleration_over_dist',
       'mean_smoothness', 'std_smoothness', 'min_smoothness', 'max_smoothness',
       'area_under_curve'],
      dtype='object')
Starting processing for subject 6
Starting processing for subject 7
Starting processing for subject 2
Starting processing for subject 3
Starting processing for subject 5
------------------- Starting SVC --------------------
Starting processing for subject 9
> Feature Scaling time: 0.238s
Starting processing for subject 8
------------------- Starting SVC --------------------
------------------- Starting SVC --------------------
------------------- Starting SVC --------------------
------------------- Starting SVC --------------------
> Feature Scaling time: 0.191s
> Feature Scaling time: 0.243s
------------------- Starting SVC --------------------
> Feature Scaling time: 0.155s
------------------- Starting SVC --------------------
> Feature Scaling time: 0.238s
------------------- Starting SVC --------------------
> Feature Scaling time: 0.192s
> Feature Scaling time: 0.179s
> Feature Scaling time: 0.167s
------------------- Starting SVC --------------------
------------------- Starting SVC --------------------
> Feature Scaling time: 0.159s
> Feature Scaling time: 0.214s
> SVC Fit time: 1840.246s
> SVC Fit time: 1910.548s
> SVC Predict time: 85.09s
> SVC Can process 434.267 events / second

SVC subject 2 Validation details:
Accuracy: 0.968, Precision: 0.949, Recall: 0.988, F1: 0.968
[[17547   973]
 [  223 18209]]
FAR : 0.055 FRR: 0.012 ERR: 0.034
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.95      0.97     18520
         1.0       0.95      0.99      0.97     18432

    accuracy                           0.97     36952
   macro avg       0.97      0.97      0.97     36952
weighted avg       0.97      0.97      0.97     36952

------------- Finished SVC on subject 2 -------------
Starting processing for subject 10
------------------- Starting SVC --------------------
> Feature Scaling time: 0.182s
> SVC Predict time: 102.682s
> SVC Can process 312.468 events / second

SVC subject 7 Validation details:
Accuracy: 0.943, Precision: 0.905, Recall: 0.988, F1: 0.945
[[14522  1651]
 [  185 15727]]
FAR : 0.112 FRR: 0.011 ERR: 0.062
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.90      0.94     16173
         1.0       0.90      0.99      0.94     15912

    accuracy                           0.94     32085
   macro avg       0.95      0.94      0.94     32085
weighted avg       0.95      0.94      0.94     32085

------------- Finished SVC on subject 7 -------------
Starting processing for subject 11
------------------- Starting SVC --------------------
> Feature Scaling time: 0.188s
> SVC Fit time: 2954.971s
> SVC Fit time: 2966.835s
> SVC Predict time: 144.549s
> SVC Can process 270.095 events / second

SVC subject 4 Validation details:
Accuracy: 0.94, Precision: 0.902, Recall: 0.987, F1: 0.943
[[17538  2073]
 [  260 19171]]
FAR : 0.116 FRR: 0.012 ERR: 0.064
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.89      0.94     19611
         1.0       0.90      0.99      0.94     19431

    accuracy                           0.94     39042
   macro avg       0.94      0.94      0.94     39042
weighted avg       0.94      0.94      0.94     39042

------------- Finished SVC on subject 4 -------------
> SVC Predict time: 133.379s
> SVC Can process 332.159 events / second

SVC subject 0 Validation details:
Accuracy: 0.962, Precision: 0.94, Recall: 0.987, F1: 0.963
[[20911  1383]
 [  289 21720]]
FAR : 0.065 FRR: 0.013 ERR: 0.039
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.94      0.96     22294
         1.0       0.94      0.99      0.96     22009

    accuracy                           0.96     44303
   macro avg       0.96      0.96      0.96     44303
weighted avg       0.96      0.96      0.96     44303

------------- Finished SVC on subject 0 -------------
Starting processing for subject 12
------------------- Starting SVC --------------------
> Feature Scaling time: 0.166s
> SVC Fit time: 3116.817s
Starting processing for subject 13
------------------- Starting SVC --------------------
> Feature Scaling time: 0.134s
> SVC Fit time: 3221.059s
> SVC Predict time: 146.164s
> SVC Can process 311.747 events / second

SVC subject 6 Validation details:
Accuracy: 0.963, Precision: 0.938, Recall: 0.991, F1: 0.964
[[21528  1485]
 [  207 22346]]
FAR : 0.068 FRR: 0.009 ERR: 0.038
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.94      0.96     23013
         1.0       0.94      0.99      0.96     22553

    accuracy                           0.96     45566
   macro avg       0.96      0.96      0.96     45566
weighted avg       0.96      0.96      0.96     45566

------------- Finished SVC on subject 6 -------------
Starting processing for subject 14
------------------- Starting SVC --------------------
> Feature Scaling time: 0.133s
> SVC Predict time: 155.433s
> SVC Can process 301.262 events / second

SVC subject 1 Validation details:
Accuracy: 0.961, Precision: 0.937, Recall: 0.988, F1: 0.962
[[22067  1549]
 [  283 22927]]
FAR : 0.069 FRR: 0.012 ERR: 0.04
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.93      0.96     23616
         1.0       0.94      0.99      0.96     23210

    accuracy                           0.96     46826
   macro avg       0.96      0.96      0.96     46826
weighted avg       0.96      0.96      0.96     46826

------------- Finished SVC on subject 1 -------------
> SVC Fit time: 3531.324s
> SVC Predict time: 151.123s
> SVC Can process 272.182 events / second

SVC subject 3 Validation details:
Accuracy: 0.952, Precision: 0.93, Recall: 0.976, F1: 0.953
[[19217  1496]
 [  490 19930]]
FAR : 0.076 FRR: 0.023 ERR: 0.05
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.93      0.95     20713
         1.0       0.93      0.98      0.95     20420

    accuracy                           0.95     41133
   macro avg       0.95      0.95      0.95     41133
weighted avg       0.95      0.95      0.95     41133

------------- Finished SVC on subject 3 -------------
> SVC Fit time: 3740.688s
> SVC Predict time: 147.896s
> SVC Can process 332.93 events / second

SVC subject 8 Validation details:
Accuracy: 0.966, Precision: 0.947, Recall: 0.986, F1: 0.966
[[23481  1336]
 [  354 24068]]
FAR : 0.056 FRR: 0.014 ERR: 0.035
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.95      0.97     24817
         1.0       0.95      0.99      0.97     24422

    accuracy                           0.97     49239
   macro avg       0.97      0.97      0.97     49239
weighted avg       0.97      0.97      0.97     49239

------------- Finished SVC on subject 8 -------------
> SVC Fit time: 1208.269s
> SVC Predict time: 40.472s
> SVC Can process 871.456 events / second

SVC subject 13 Validation details:
Accuracy: 0.977, Precision: 0.963, Recall: 0.993, F1: 0.978
[[16980   665]
 [  132 17493]]
FAR : 0.039 FRR: 0.007 ERR: 0.023
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.96      0.98     17645
         1.0       0.96      0.99      0.98     17625

    accuracy                           0.98     35270
   macro avg       0.98      0.98      0.98     35270
weighted avg       0.98      0.98      0.98     35270

------------ Finished SVC on subject 13 -------------
> SVC Fit time: 4657.845s
> SVC Predict time: 141.2s
> SVC Can process 321.346 events / second

SVC subject 9 Validation details:
Accuracy: 0.932, Precision: 0.895, Recall: 0.977, F1: 0.934
[[20309  2576]
 [  515 21974]]
FAR : 0.124 FRR: 0.021 ERR: 0.072
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.89      0.93     22885
         1.0       0.90      0.98      0.93     22489

    accuracy                           0.93     45374
   macro avg       0.94      0.93      0.93     45374
weighted avg       0.94      0.93      0.93     45374

------------- Finished SVC on subject 9 -------------
> SVC Fit time: 3503.107s
> SVC Fit time: 2422.128s
> SVC Predict time: 99.985s
> SVC Can process 463.792 events / second

SVC subject 10 Validation details:
Accuracy: 0.949, Precision: 0.916, Recall: 0.988, F1: 0.951
[[21395  2078]
 [  274 22625]]
FAR : 0.096 FRR: 0.011 ERR: 0.054
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.91      0.95     23473
         1.0       0.92      0.99      0.95     22899

    accuracy                           0.95     46372
   macro avg       0.95      0.95      0.95     46372
weighted avg       0.95      0.95      0.95     46372

------------ Finished SVC on subject 10 -------------
> SVC Predict time: 72.79s
> SVC Can process 638.683 events / second

SVC subject 12 Validation details:
Accuracy: 0.964, Precision: 0.937, Recall: 0.994, F1: 0.965
[[21981  1525]
 [  149 22835]]
FAR : 0.069 FRR: 0.006 ERR: 0.038
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.94      0.96     23506
         1.0       0.94      0.99      0.96     22984

    accuracy                           0.96     46490
   macro avg       0.97      0.96      0.96     46490
weighted avg       0.97      0.96      0.96     46490

------------ Finished SVC on subject 12 -------------
> SVC Fit time: 2514.038s
> SVC Predict time: 56.54s
> SVC Can process 909.076 events / second

SVC subject 14 Validation details:
Accuracy: 0.976, Precision: 0.958, Recall: 0.995, F1: 0.976
[[24815  1110]
 [  138 25336]]
FAR : 0.044 FRR: 0.005 ERR: 0.024
Report:
              precision    recall  f1-score   support

         0.0       0.99      0.96      0.98     25925
         1.0       0.96      0.99      0.98     25474

    accuracy                           0.98     51399
   macro avg       0.98      0.98      0.98     51399
weighted avg       0.98      0.98      0.98     51399

------------ Finished SVC on subject 14 -------------
> SVC Fit time: 4077.751s
> SVC Predict time: 107.845s
> SVC Can process 444.073 events / second

SVC subject 11 Validation details:
Accuracy: 0.936, Precision: 0.903, Recall: 0.976, F1: 0.938
[[21673  2479]
 [  576 23163]]
FAR : 0.111 FRR: 0.022 ERR: 0.066
Report:
              precision    recall  f1-score   support

         0.0       0.97      0.90      0.93     24152
         1.0       0.90      0.98      0.94     23739

    accuracy                           0.94     47891
   macro avg       0.94      0.94      0.94     47891
weighted avg       0.94      0.94      0.94     47891

------------ Finished SVC on subject 11 -------------
> SVC Fit time: 6451.197s
> SVC Predict time: 163.116s
> SVC Can process 391.446 events / second

SVC subject 5 Validation details:
Accuracy: 0.937, Precision: 0.904, Recall: 0.978, F1: 0.94
[[28697  3305]
 [  697 31152]]
FAR : 0.112 FRR: 0.02 ERR: 0.066
Report:
              precision    recall  f1-score   support

         0.0       0.98      0.90      0.93     32002
         1.0       0.90      0.98      0.94     31849

    accuracy                           0.94     63851
   macro avg       0.94      0.94      0.94     63851
weighted avg       0.94      0.94      0.94     63851

------------- Finished SVC on subject 5 -------------