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QUICKSTART.md

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Quick Start Guide

🚀 Get Started in 5 Minutes

Step 1: Install Dependencies

pip install -r requirements.txt

Step 2: Generate Sample Data

python generate_sample_data.py

This creates a sample dataset with 1000 patients and ~15% sepsis rate.

Step 3: Train the Model

python train.py

This will:

  • Load and preprocess the data
  • Create time-series features
  • Handle imbalanced data
  • Train the model
  • Save results

Step 4: Evaluate

python evaluate.py

Step 5: Make Predictions

python inference.py --data data/raw/sepsis_data.csv --output results/predictions.csv

📊 Expected Output

After training, you should see:

  • Model saved to models/sepsis_model.pkl
  • Feature importance plot in results/feature_importance.png
  • Test metrics in results/test_metrics.csv

🔧 Customize

Edit configs/config.yaml to:

  • Change model algorithm (xgboost, lightgbm, catboost)
  • Adjust hyperparameters
  • Modify feature engineering settings
  • Change imbalanced learning method

📚 Learn More

See README.md for detailed documentation.

🆘 Troubleshooting

Issue: ModuleNotFoundError

  • Solution: Make sure you're in the project root directory and dependencies are installed

Issue: FileNotFoundError for data

  • Solution: Run generate_sample_data.py first

Issue: Memory errors

  • Solution: Reduce n_patients in generate_sample_data.py or reduce max_features in config