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# 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
## Abstract
The purpose of the project was to select the most important features and investigate possible machine learning algorithm on the 2018 data collected through the MoTUS setup.
## Directory tree
```
├───data_extractor_scripts
│ ├───.ipynb_checkpoints
│ ├───average_data_year
│ └───data_zip
├───exploratory_analysis
├───final_submission_scripts
│ ├───.ipynb_checkpoints
│ ├───images
│ ├───py_scripts
│ │ └───.ipynb_checkpoints
│ └───__pycache__
├───intermediate_work_scripts
├───report
└───submission_folder
├───data
│ ├───average_data
│ └───zip_files
├───results
│ ├───baseline
│ │ └───images
│ ├───neural_network
│ ├───random_forest
│ ├───results_analysis
│ └───ridge_regression
│ └───images
├───scripts_data_extractor
├───scripts_features_selection
└───scripts_regression
├───.ipynb_checkpoints
└───__pycache__
```
## Overview
This repository, other than the definitive results and scripts, contains all the intermediate goals for possible future investigation of the project development. The general content of the files (mainly `.ipynb`) and folders of this directory is shown below. Subfolder readmes will be present.
- **data_extractor_scripts:** contains all the different versions of the code used to convert the raw data into the regression matrix used in the machine learning algorithms. A final regression matrix is also included.
- **exploratory_analysis:** includes all the scripts used firstly to investigate the raw data. No notable operations are performed with these scripts.
- **final_submission_scripts:** contains the scripts able to efficiently run the 3 selected regression methods. It includes all the accessory files and `.py` conversion of the notebooks used run the scripts on the laboratory server.
- **intermediate_work_scripts:** includes the intermediate file used to run the explorative version of the regression.
- **report:** contains the final report for the CS-433 course, together with its appendix and the guidelines for the project.
- **submission_folder:** includes the final version of all the script necessary to produce the conclusion present in the report starting from the raw data.
- *SCRIPTS_RULES.txt:* general rules and procedures used throughout the project.
**IMPORTANT: For working scripts and clean results always refer to `/submission_folder`. All codes have appropriate readmes and are adequately commented.**
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