Release v0.25.0 · sebp/scikit-survival

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.

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_ in sksurv.linear_model.CoxnetSurvivalAnalysis with a detailed mathematical definition (#541).
Standardize the description of the structured survival array y across 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 alphas sequence is automatically generated in sksurv.linear_model.CoxnetSurvivalAnalysis.
Fix pandas warnings in example code.
Update links to external documentation, including scikit-learn and numpy.

Full Changelog: v0.24.1...v0.25.0