What’s new in 0.25#
scikit-survival 0.25.0 (2025-08-21)#
This release adds support for scikit-learn 1.7 and overhauls the API documentation to improve clarity and consistency.
Enhancements#
Add support for scikit-learn 1.7 (#532).
Move tox configuration to pyproject.toml.
Add PEP 735 dependency groups for optional dependencies.
Modernize C++ syntax in the coxnet model, improving code clarity and maintainability (#526).
Add license-files field to pyproject.toml (PEP 639).
Add artifact attestation for sdist and wheel files.
Update CI infrastructure to use the latest runners and tools, including check-jsonschema, ruff, and uv.
Update CI infrastructure to use miniforge to avoid licensing issues related to Anaconda’s default channels (#542).
Add running doctest to CI.
Bump versions of dependencies on Binder.
Documentation#
Overhaul the entire API documentation for improved clarity, consistency, and user experience. This includes updated docstrings for all major modules, including ensemble, linear_model, svm, tree, metrics, and nonparametric (#539).
For examples with matplotlib plots, include the plot as a static image in the documentation (#543).
Clarify what inputs each metric expects and add a graphical overview to Evaluating Survival Models (#535).
Clarify the calculation of the
deviance_ratio_insksurv.linear_model.CoxnetSurvivalAnalysiswith a detailed mathematical definition (#541).Standardize the description of the structured survival array
yacross the library.Clarify that an exception is raised for out-of-range test times when the censoring distribution cannot be estimated (#524).
Explain how the
alphassequence is automatically generated insksurv.linear_model.CoxnetSurvivalAnalysis.Fix pandas warnings in example code.
Update links to external documentation, including scikit-learn and numpy.