scikit-survival
CommunitySurvival analysis with scikit-survival in Python
Authorovachiever
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Comprehensive survival analysis tooling in Python, including Cox models, ensemble methods, survival SVMs, and evaluation metrics.
Core Features & Use Cases
- ✅ CoxPH, Coxnet, and AFT models
- ✅ RandomSurvivalForest, GradientBoostingSurvivalAnalysis
- ✅ Survival SVMs and distance-based methods
- ✅ Evaluation metrics: C-index, time-dependent AUC, Brier score
Quick Start
Load survival data, fit a model (e.g., CoxPHSurvivalAnalysis), and evaluate predictive performance.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: scikit-survival Download link: https://github.com/ovachiever/droid-tings/archive/main.zip#scikit-survival Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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