Cs 433 Machine Learning Project I : Higgs Challenge

This is the result of the project I for the course cs 433 Machine Learning at EPFL. The model developed is able to classify the events (signal or noise) relevant for the detection of the Higgs Boson. More info in https://www.kaggle.com/c/higgs-boson/leaderboard

Getting Started

Git clone the repository. https://github.com/Idate96/cs_433_ML_project_1.git To run the model:

python run.py

It will reproduce the best results obtained with it. They are saved in the folder dataset under the name submission_0x.csv.

Prerequisites

python  3.6x
numpy  1.13.x

Running the tests

nosetests --verbose Do we need this?

Architecture of the code


-src
--run.py # main
--ensemble_log_regression.py # contains the regression model
--utils.py # helper function to process and load data
--implementations.py # contains the implementation of ML_methods
--test_ML_methods # contains the dataset used during the lab sessions
--old_models # old_models considered for the assignment
-dataset # contains the dataset for the competition and the submission for kaggle
-config #where the weight of the model are saved

Authors

Lorenzo Terenzi
Alberto Bonifazi
Laura Jou Ferrer