Release v0.23.0 · sebp/scikit-survival

This release adds support for scikit-learn 1.4 and 1.5, which includes missing value support for sksurv.ensemble.RandomSurvivalForest.

Moreover, this release fixes critical bugs. When fitting sksurv.tree.SurvivalTree, the sample_weight is now correctly considered when computing the log-rank statistic for each split. This change also affects sksurv.ensemble.RandomSurvivalForest and sksurv.ensemble.ExtraSurvivalTrees which pass sample_weight to the individual trees in the ensemble.

This release fixes a bug in sksurv.ensemble.ComponentwiseGradientBoostingSurvivalAnalysis and sksurv.ensemble.GradientBoostingSurvivalAnalysis when dropout is used. Previously, dropout was only applied starting with the third iteration, now dropout is applied in the second iteration too.

Finally, this release adds compatibility with numpy 2.0 and drops support for Python 3.8.

Bug fixes

Fix issue with dropout in sksurv.ensemble.ComponentwiseGradientBoostingSurvivalAnalysis and sksurv.ensemble.GradientBoostingSurvivalAnalysis, where it was only applied starting with the third iteration.
Fix LogrankCriterion in sksurv.tree.SurvivalTree to handle sample_weight correctly (#464).

Fix deprecations with pandas 2.2.
Drop importlib-resources dependency.
Add support for scikit-learn 1.4 (#441).
Add warm_start support to sksurv.ensemble.ComponentwiseGradientBoostingSurvivalAnalysis.
Add missing values support to sksurv.ensemble.RandomSurvivalForest.
Add require_y tag to sksurv.base.SurvivalAnalysisMixin.
Upgrade to ruff 0.4.3 (#456).
Add support for scikit-learn 1.5 (#461).

Fix sksurv.nonparametric.kaplan_meier_estimator() documentation to give correct default value for conf_type (#430).
Fix allowed values for kernel in sksurv.svm.FastSurvivalSVM and sksurv.svm.MinlipSurvivalAnalysis (#444).
Fix typo in API doc of sksurv.ensemble.RandomSurvivalForest and sksurv.ensemble.ExtraSurvivalTrees (#446).
Fix API doc for the criterion parameter of sksurv.ensemble.GradientBoostingSurvivalAnalysis (#449).
Update links to scipy, pandas and numpy documentation.
Fix letter of hyper-parameter used in the formula for sksurv.linear_model.IPCRidge (#454).
Upgrade Sphinx to 7.3 and pydata-sphinx-theme to 0.15 (#455).

Full Changelog: v0.22.2...v0.23.0