XGBoost Survival Embeddings

Survival Analysis is a powerful statistical technique with a wide range of applications such as predictive maintenance, customer churn, credit risk, asset liquidity risk, and others.

However, it has not yet seen widespread adoption in industry, with most implementations embracing one of two cultures:

1. models with sound statistical properties, but lacking in expressivess and computational efficiency
2. highly efficient and expressive models, but lacking in statistical rigor

xgbse aims to unite the two cultures in a single package, adding a layer of statistical rigor to the highly expressive and computationally effcient xgboost survival analysis implementation.

The package offers:

• calibrated and unbiased survival curves with confidence intervals (instead of point predictions)
• great predictive power, competitive to vanilla xgboost
• efficient, easy to use implementation
• explainability through prototypes