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.
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Installation
View all platforms →skilz install davila7_claude-code-templates/scikit-survival skilz install davila7_claude-code-templates/scikit-survival --agent opencode skilz install davila7_claude-code-templates/scikit-survival --agent codex skilz install davila7_claude-code-templates/scikit-survival --agent gemini
First time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/davila7/claude-code-templates cp -r claude-code-templates/cli-tool/components/skills/scientific/scikit-survival ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Details
- Owner
- davila7
- Repository
- claude-code-templates
- Stars
- 13,835
- Forks
- 1,200
- Type
- Technical
- Meta-Domain
- data ai
- Primary Domain
- machine learning
- Sub-Domain
- learning models model
- Skill Size
- 74.0 KB
- Files
- 7
- Quality Score
- 66.7
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