search

sktime / skpro

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
https://skpro.readthedocs.io/en/latest
BSD 3-Clause "New" or "Revised" License
250 stars 46 forks source link

[MNT] [Dependabot](deps): Update scikit-survival requirement from <0.23.0 to <0.24.0 #419

Closed dependabot[bot] closed 5 months ago

dependabot[bot] commented 5 months ago

Updates the requirements on scikit-survival to permit the latest version.

Release notes

Sourced from scikit-survival's releases.

v0.23.0

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

Enhancements

Documentation

Backwards incompatible changes

  • Drop support for Python 3.8 (#427).

New Contributors

Full Changelog: https://github.com/sebp/scikit-survival/compare/v0.22.2...v0.23.0

Commits
  • 1675df8 DOC: Update install command to use conda-forge
  • 43dfc48 CI: Test with numpy 2.0
  • 3fc07d6 DOC: Add release notes for 0.23.0
  • 8df1f51 DOC: Link to docs of scikit-learn 1.5
  • 34b410a Use numpy 2.0 stable release as build requirement
  • 3bc8373 Use same minimum Cython version in dependencies
  • 8305e7a Merge pull request #464 from sebp/fix/443
  • 769ea89 FIX LogrankCriterion does not consider sample_weights
  • 1bcd8d0 Merge pull request #462 from sebp/dependabot/github_actions/pypa/cibuildwheel...
  • 7541329 CI: Install numpy 1.X when testing wheels
  • Additional commits viewable in compare view


Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show ignore conditions` will show all of the ignore conditions of the specified dependency - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)