scikit-survival-analysis
From the author
Time-to-event modeling with scikit-survival: Cox PH (elastic net), Random Survival Forests, Boosting, SVMs for censored data. C-index, Brier, time-dependent AUC; Kaplan-Meier, Nelson-Aalen, competing risks. Pipeline/GridSearchCV compatible. Use statsmodels for frequentist, pymc for Bayesian, lifelines for parametric.
Install
npx skills add jaechang-hits/SciAgent-Skills --skill scikit-survival-analysis -a claude-code
Installs to .claude/skills/scikit-survival-analysis/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (GPL-3.0) does not let us redistribute its files. The install commands fetch them from GitHub instead.
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