.. currentmodule:: sklr

.. _release_notes_0_3:

===========
Version 0.3
===========

scikit-lr has been rewritten on top of the current scikit-learn API.

.. include:: changelog_legend.inc

.. towncrier release notes start

.. _changes_0_3_0:

Version 0.3.0
=============

**In development**

* The extension modules extend the internals of scikit-learn, so scikit-lr is
  built against a single minor release of scikit-learn, 1.9, and importing
  :mod:`sklr` with another one raises an :class:`ImportError`.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

* There are wheels for Linux (x86_64 and aarch64), macOS (x86_64 and arm64)
  and Windows (AMD64 and ARM64).
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

* The public API has type hints, which type checkers find in the installed package
  (:pep:`561`).
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

* scikit-lr requires Python 3.13 or later, and is built with meson-python.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

:mod:`sklr`
-----------

* |Feature| :func:`show_versions` prints the versions of scikit-lr, of the scikit-learn that
  it was built against and of the dependencies, to include them in bug reports.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

:mod:`sklr.base`
----------------

* |Feature| :class:`base.LabelRankerMixin` and :class:`base.PartialLabelRankerMixin` set the
  tags of the label rankers and of the partial label rankers, and their ``score``
  method computes :func:`metrics.kendall_tau_score` and :func:`metrics.tau_x_score`
  on the predictions of the ranker.
  :func:`base.is_label_ranker` and :func:`base.is_partial_label_ranker` tell them
  apart from other estimators.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

:mod:`sklr.metrics`
-------------------

* |Feature| :func:`metrics.kendall_tau_score` and :func:`metrics.kendall_distance` compare
  label rankings, and :func:`metrics.tau_x_score` compares partial label rankings,
  averaging over the samples with optional sample weights.
  :func:`metrics.get_scorer` gets their scorers by name, to pass them to the
  ``scoring`` parameter of the model selection tools of scikit-learn, and
  :func:`metrics.get_scorer_names` lists the names.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

:mod:`sklr.utils`
-----------------

* |Feature| :func:`utils.type_of_ranking` determines whether a target holds label rankings,
  partial label rankings or does not encode rankings, following the representation
  described in :ref:`ranking_representation`.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`

* |Feature| :func:`utils.check_ranking` validates the rankings of a target and converts them
  to a ``float64`` array, rejecting rankings with ties and incomplete rankings
  unless they are allowed.
  By :user:`Juan Carlos Alfaro Jiménez <alfaro96>`. :pr:`99`