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πŸ”­ πŸ“ˆ Supervised Machine Learning techniques used to categorise Higgs boson events using data collected from the Large Hadron Collider, CERN.

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louisheery/higgs-ML

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Higgs ML (Higgs boson Machine Learning Classifiers)

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Supervised Machine Learning techniques used to categorise VH, H(bb) Higgs boson decay events using data collected from the Large Hadron Collider, CERN.

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Repo Contents

a) Different BDT Classifiers

b) XGBoost Optimisation

c) Dataset Analysis

a) Dijet-mass Aware ANN

b) Monte Carlo Generator Aware ANN

a) H(bb) Monte Carlo Generated Event Dataset

b) Graph Plotting Files

  • bdtPlotting.py – Scripts used to plot Boosted Decision Tree (BDT) Output Graphs.
  • nnPlotting.py – Scripts used to plot Neural Network (NN) and Adversarial Neural Network (ANN) Output Graphs.
  • sensitivity.py – Scripts used to calculate sensitivity of BDT and NN and ANN Classifiers.

Download Repo

  • Download Link is HERE

  • Fork Repo using:

$ git clone https://github.com/louisheery/higgs-ML.git

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πŸ”­ πŸ“ˆ Supervised Machine Learning techniques used to categorise Higgs boson events using data collected from the Large Hadron Collider, CERN.

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