What’s new in 0.24#

scikit-survival 0.24.1 (2025-03-25)#

This release restricts the version of osqp to versions prior to 1.0.0.

This release adds support for scikit-learn 1.6, which includes missing-values support for sksurv.ensemble.ExtraSurvivalTrees. Moreover, the release features sksurv.nonparametric.cumulative_incidence_competing_risks() which implements a non-parameteric estimator of the cumulative incidence function for competing risks. See the user guide on the analysis of competing risks.

In the C++ code of sksurv.linear_model.CoxnetSurvivalAnalysis, set type of n_alphas to VectorType::Index instead of ìnt, because on Windows, int and Eigen’s Index differ in size.
Fix printing of Python version in sksurv.show_versions().
Give an error if max_sample is set, but bootstrap is False in sksurv.ensemble.RandomSurvivalForest and sksurv.ensemble.ExtraSurvivalTrees.

Add sksurv.nonparametric.cumulative_incidence_competing_risks() to estimate the cumulative incidence function in the case of competing risks (#491, #500).
Add sksurv.datasets.load_bmt() and sksurv.datasets.load_cgvhd() which are datasets with competing risks (#491, #500).
Add missing-values support to sksurv.ensemble.ExtraSurvivalTrees (#504).
Add estimators_samples_ property to sksurv.ensemble.RandomSurvivalForest and sksurv.ensemble.ExtraSurvivalTrees.
Upgrade syntax to Python 3.10.
Run nbval with Python 3.12, matplotlib 3.9, and seaborn 0.13.