What’s new in 0.20

scikit-survival 0.20.0 (2023-03-05)

This release adds support for scikit-learn 1.2 and drops support for previous versions.

Enhancements

• Raise more informative error messages when a parameter does not have a valid type/value (see sklearn#23462).

• Add positive and random_state parameters to sksurv.linear_model.IPCRidge.

Documentation

• Update API docs based on scikit-learn 1.2 (where applicable).

Backwards incompatible changes

• To align with the scikit-learn API, many parameters of estimators must be provided with their names, as keyword arguments, instead of positional arguments.

• Remove deprecated normalize parameter from sksurv.linear_model.IPCRidge.

• Remove deprecated X_idx_sorted argument from sksurv.tree.SurvivalTree.fit().

• Setting kernel="polynomial" in sksurv.svm.FastKernelSurvivalSVM, sksurv.svm.HingeLossSurvivalSVM, and sksurv.svm.MinlipSurvivalAnalysis has been replaced with kernel="poly".