This project was made to answer this lab's questions: TP3 .It aims to:
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Getting started with Python's scikit-learn library, dedicated to machine learning.
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Becoming familiar with the evaluation of models learned in supervised classification.
These are the steps to follow in order to perform tests and choose the appropriate classifier in supervised learning
- Splitting our dataset into two parts: 2/3 for training and 1/3 for testing (in general)
- Training our model on the training set which provides a prediction on the test set
- Testing results on the test set (calculating error/accuracy...)
Cross validation may be applied to ensure more accuracy to our prediction results
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Python3 installed
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The different required dependencies are found in this file requirements.txt.Run this command to install them:
pip install -r requirements/requirements.txt