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Project for Machine Learning Data Mining course

License: MIT License

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adaboost data-mining data-preprocessing-pipelines decision-tree extra-trees k-neighbors linear-kernel machine-learning numpy pandas

obesity-estimator's Introduction

Obesity-estimator

Python numpy scikit-learn

This is a project made for the course of Machine Learning and Data Mining at University of Brescia.

The problem chosen is the prediction of the obesity level of some people given information about their eating habits and level of physical activity.

The goal of the project is to create a classifier model and analyze the results of different classifiers.

The dataset used can be found here.

In our project we used these classifiers:

  • Decision Trees
  • Support Vector Machines
  • K-Neighbors
  • Random Forest
  • Extra Trees
  • Voting Classifier
  • Adaboost

More information about the implementation and results can be found in this notebook.

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