What’s new in 0.23#
scikit-survival 0.23.1 (2024-11-04)#
This release adds support for Python 3.13. The minimum required version for pandas has been bumped to pandas 1.4.0.
Bug fixes#
Add SurvivalAnalysisMixin base class to
sksurv.ensemble.ExtraSurvivalTreesto enable thesksurv.ensemble.ExtraSurvivalTrees.score()method that has been unintentionally removed in 0.23.0 (#488).
Enhancements#
Improve performance of
sksurv.metrics.concordance_index_censored()andsksurv.metrics.concordance_index_ipcw()(#465).
Backwards incompatible changes#
Support for pandas versions before 1.4.0 has been dropped.
scikit-survival 0.23.0 (2024-06-30)#
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.ComponentwiseGradientBoostingSurvivalAnalysisandsksurv.ensemble.GradientBoostingSurvivalAnalysis, where it was only applied starting with the third iteration.Fix LogrankCriterion in
sksurv.tree.SurvivalTreeto handle sample_weight correctly (#464).
Enhancements#
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).
Documentation#
Fix
sksurv.nonparametric.kaplan_meier_estimator()documentation to give correct default value for conf_type (#430).Fix allowed values for kernel in
sksurv.svm.FastSurvivalSVMandsksurv.svm.MinlipSurvivalAnalysis(#444).Fix typo in API doc of
sksurv.ensemble.RandomSurvivalForestandsksurv.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).
Backwards incompatible changes#
Drop support for Python 3.8 (#427).