MoTUS machine learning approach - Machine Learning Project 2

Machine learning Project 2 Option A – CS-433 – EPFL<br> Fall 2018<br> *Authors:* Gianluca Mancini, Tullio Nutta and Tianchu Zhang<br> *Laboratory:* LESO-PB – Solar Energy and Building Physics Laboratory<br> *Supervisors:* Roberto Castello and Dasaraden Mauree

Scripts outline

Almost definitive scripts of all the available methods. helpers.py provides accessory functions fo the scripts.

• 1. Folders and files outline
• *images:* empty folder. Target directory in which images are saved running baseline or ridge regression.

• *py_scripts:* directory where .py and .sh bash file are saved before running them on the server.

• *feature_for_ridge and feature_for_ridge_season:* different versions of features selected with random forest method. Used with a possible configuration of baseline.ipynb and ridge_regression.ipynb.