Usage

1. Clone the repository or download the code files.
2. Ensure that you have the "ObesityDataSet.csv" file in the same directory as the code files or update the file path accordingly.
3. Run the code using Apache Spark or a Jupyter Notebook environment.

The code performs the following tasks:

1. Data loading and exploration
2. Data preprocessing and feature engineering
3. Model training and evaluation
4. Results analysis and visualization

Models

The following machine learning models are implemented and evaluated for obesity prediction:

• Logistic Regression
• Random Forest Classifier

You can modify the code to experiment with different models or hyperparameter tuning.

Evaluation

The models are evaluated using various metrics, including:

• Accuracy
• Test Error
• Confusion Matrix

The code provides detailed instructions and comments to guide you through the evaluation process.

Acknowledgments

• The dataset used in this project is from [Source].
• This project was inspired by [Inspiration/Reference].