Supervised Learning for Napoleonic Strategy

This project applies supervised learning techniques to predict the outcomes of Napoleonic battles based on historical data.

Project Structure

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/supervised-learning.git
   cd supervised-learning

2. Install dependencies using Poetry:

   poetry install

Usage

1. Run the prediction script:

   poetry run python src/battle_predict.py

2. Output: The script will print the accuracy and classification report of the model.

Data

The dataset battles.csv contains historical data of Napoleonic battles with the following columns:

• Battle Name
• Date
• Commander
• Troop Strength
• Opponent Commander
• Opponent Strength
• Terrain
• Weather
• Strategy Used
• Outcome

Model

The model uses a Random Forest Classifier to predict the outcome of battles. The features used for prediction include:

• Troop Strength
• Opponent Strength
• Terrain
• Weather
• Troop Ratio (derived feature)

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Gareth Murphy - [email protected]

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

Acknowledgements

• Pandas
• Scikit-learn