$$Multi-Class \space Prediction \space of \space Obesity \space Risk$$

Project Description

This repository contains the code and materials for our Machine Learning project on "Multi-Class Prediction of Obesity Risk".
In this project, we focused on predicting the risk of obesity using a multi-class classification approach. Our work involved various stages including exploratory data analysis (EDA), feature engineering, and building predictive models using a diverse set of machine learning algorithms and choose the best model for our pipeline.

Key Components

• Exploratory Data Analysis (EDA): We thoroughly examined the dataset to understand its underlying patterns and distributions.
• Feature Engineering: We engineered relevant features to enhance the predictive power of our models.
• Modeling: We implemented multiple machine learning models including Logistic Regression, Decision Tree, Random Forest, SVC, KNN Classifier, XGBoost, LGBM, Catboost, and Adaboost and choose the best one.
• Pipeline: We utilized a pipeline to streamline our machine learning workflow and ensure reproducibility.

Repository Structure

• Data/: Contains the dataset used in the project, the submission file and the Presentation slides summarizing our project findings.
• Preprocessing/: unfinished Jupyter notebooks containing the code for EDA, feature engineering, and modeling and picture of submission on Kaggle competition.
• Multi_Class Prediction of Obesity Risk: Jupyter notebooks containing the code for EDA, feature engineering, and modeling.
• README.md: You are here! It provides an overview of the project and instructions for replicating our work.

Getting Started

To replicate our project, follow these steps:

1. Clone this repository to your local machine.
2. Navigate to the Multi_Class Prediction of Obesity Risk Jupyter notebook.
3. Open the Jupyter notebooks and execute the code cells sequentially.
4. Refer to the presentation slides in the Data/ directory for a summary of our findings.

Additional Resources

• Kaggle: [Kaggle Competition]

Authors

This project was created by:
1. Amina Mohamed
2. Ashraf Mahmoud
3. Nagham Ehab
4. Shorouq Hossam