scikit-survival
Builds, evaluates, and audits right-censored survival analysis workflows with scikit-survival (sksurv): Cox PH, Coxnet, IPC ridge, survival trees, forests, boosting, and SVMs, plus nonparametric cumulative incidence for competing risks. Covers leakage-safe scikit-learn pipelines, nested CV, and censoring-aware metrics. Use when fitting survival models on time-to-event data, building structured outcome arrays, computing IPCW concordance, dynamic AUC, or Brier scores, estimating cause-specific cumulative incidence, or tuning models without leakage. Not for Fine-Gray regression, which scikit-survival does not provide.
- Version
- 1.2
- License
- MIT
- Compatibility
- Requires Python 3.11+, uv, and the pinned scikit-survival 0.28.0 stack for executable examples. Bundled CLIs are local and network-free by default.
Pinned to revision df088027ff23, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
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- Bash
Files
- skills/scikit-survival/SKILL.md
- skills/scikit-survival/references/competing-risks.md
- skills/scikit-survival/references/cox-models.md
- skills/scikit-survival/references/data-handling.md
- skills/scikit-survival/references/ensemble-models.md
- skills/scikit-survival/references/evaluation-metrics.md
- skills/scikit-survival/references/svm-models.md
- skills/scikit-survival/scripts/_common.py
- skills/scikit-survival/scripts/competing_risk_cif.py
- skills/scikit-survival/scripts/evaluate_survival_metrics.py
- skills/scikit-survival/scripts/model_report.py
- skills/scikit-survival/scripts/train_survival_model.py
- skills/scikit-survival/scripts/validate_survival_csv.py
Every link opens the file at its source, pinned to the revision this page describes.