- Clone the repository or download the code files.
- Ensure that you have the "ObesityDataSet.csv" file in the same directory as the code files or update the file path accordingly.
- Run the code using Apache Spark or a Jupyter Notebook environment.
The code performs the following tasks:
- Data loading and exploration
- Data preprocessing and feature engineering
- Model training and evaluation
- Results analysis and visualization
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.
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.
- The dataset used in this project is from [Source].
- This project was inspired by [Inspiration/Reference].