In this project, we aim at solving the Higgs Boson classification, a problem posed by the CERN.
In the this folder are the following files: |'run.py'| A main script containing our best method chosen to solve this classification problem : Ridge Regression In order to run this scrpit you need to have the test.csv and train.csv in this very same folder.
|'implementations.py'| A file containing our implementation of 6 machine learning regression and classification algorithms
- least squares
- least squares Gradient Descent
- least squares Stochastic Gradient Descent
- Ridge Regression
- Logistic regression
- Regularized logistic regression
|'proj1_helpers'| A file containing all other additional necessary functions used for
- loading the data
- preprocessing
- splitting the data
- batch iteration
|'cross_validation'| A file containing all required functions for cross validation
- build_k_indices
- k_fold_cross_validation
- ridge_reg_cross_validation
- reg_log_regression_cross_validation
The following 'Python 3' packages are necessary for running our project : 'numpy'
Team name : 'Outliers' Our team on is accessible with the following link : https://www.aicrowd.com/challenges/epfl-machine-learning-higgs/teams/Outliers Our best result is :
- Categorical accuracy of 0.830
- F1 score of 0.740
Chabenat Eugénie : eugenie.chabenat@epfl.ch Djambazovska Sara : sara.djambazovka@epfl.ch Mamooler Sepideh : sepideh.mamooler@epfl.ch