scikit-survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
This page mirrors an upstream repository entry. It does not mean the skill is already part of the SCI Skills curated catalog.
- Raw path
- scientific-skills/scikit-survival
- Allowed tools
- -
- Repository version
- 2.31.0
- Synced at
- March 27, 2026
About this skill
About this skill
scikit-survival is a Python library for survival analysis built on top of scikit-learn. It provides specialized tools for time-to-event analysis, handling the unique challenge of censored data where some observations are only partially known.
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