├── src/
│ ├── player_clustering/ # Trains clustering model and applies it to new data set
│ │ ├── cluster_config.py # Specify key paramaters for training and test data
│ │ ├── clusterer.py # Core clustering logic
│ │ ├── clean_and_load_data.py# Data preprocessing
│ │ ├── train_model.py # Training pipeline
│ │ └── predict_on_newdata.py # Prediction pipeline
├── docs/
│ └── usage.md # Detailed usage instructions
└── README.md # Project overview```
## Quick Start
For end users:
1. To classify new players: Use `predict_on_newdata.py`
2. To retrain the model: Use `train_model.py`
## Usage Flow
1. `predict_on_newdata.py` and `train_model.py` are the main entry points
2. These files use `clusterer.py` which contains the core clustering logic
3. `clusterer.py` uses `clean_and_load_data.py` for data preprocessing