소개
The scikit-survival skill empowers Claude to handle complex time-to-event datasets where observations are frequently censored. It provides a comprehensive framework for implementing everything from traditional Cox Proportional Hazards models to modern machine learning approaches like Random Survival Forests and Gradient Boosting. By integrating specialized evaluation metrics such as the Concordance Index and Brier score, this skill ensures that your survival models are both accurate and properly validated for real-world applications in medicine, finance, or engineering.
