Obesity Prediction Using Random Forest

Overview

This project utilizes the Random Forest algorithm implemented in MATLAB to predict obesity based on various features collected from a dataset. The model is trained using a set of training data and then tested on a separate dataset to evaluate its performance. The results are formatted for submission to Kaggle.

Project Structure

• Main File:

  • proj2_og.m: The main script that performs data loading, processing, model training, and prediction.

• Variations and Experiments: Additional scripts that explore different modeling techniques and configurations.

• Data Files: The project uses two CSV files:

  • train.csv: Contains the training data.
  • test.csv: Contains the testing data.

Prerequisites

• MATLAB installed on your machine.
• Required toolboxes for statistics and machine learning.