v1.2.rst

.. currentmodule:: sklearn

Version 1.2.0

In Development

Changed models

The following estimators and functions, when fit with the same data and parameters, may produce different models from the previous version. This often occurs due to changes in the modelling logic (bug fixes or enhancements), or in random sampling procedures.

Changelog

:mod:`sklearn.cluster`

• |Enhancement| The predict and fit_predict methods of :class:`cluster.OPTICS` now accept sparse data type for input data. :pr:`14736` by :user:`Hunt Zhan <huntzhan>`, :pr:`20802` by :user:`Brandon Pokorny <Clickedbigfoot>`, and :pr:`22965` by :user:`Meekail Zain <micky774>`.
• |Enhancement| :class:`cluster.Birch` now preserves dtype for numpy.float32 inputs. :pr:`22968` by Meekail Zain <micky774>.

:mod:`sklearn.datasets`

• |Enhancement| Introduce the new parameter parser in :func:`datasets.fetch_openml`. parser="pandas" allows to use the very CPU and memory efficient pandas.read_csv parser to load dense ARFF formatted dataset files. It is possible to pass parser="liac-arff" to use the old LIAC parser. When parser="auto", dense datasets are loaded with "pandas" and sparse datasets are loaded with "liac-arff". Currently, parser="liac-arff" by default and will change to parser="auto" in version 1.4 :pr:`21938` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.ensemble`

• |Efficiency| Improve runtime performance of :class:`ensemble.IsolationForest` by avoiding data copies. :pr:`23252` by :user:`Zhehao Liu <MaxwellLZH>`.

:mod:`sklearn.metrics`

• |Feature| :func:`class_likelihood_ratios` is added to compute the positive and negative likelihood ratios derived from the confusion matrix of a binary classification problem. :pr:`22518` by :user:`Arturo Amor <ArturoAmorQ>`.

:mod:`sklearn.neighbors`

• |Enhancement| :class:`neighbors.KernelDensity` bandwidth parameter now accepts definition using Scott's and Silvermann's estimation methods. :pr:`10468` by :user:`Ruben <icfly2>` and :pr:`22993` by :user:`Jovan Stojanovic <jovan-stojanovic>`.
• |Feature| Adds new function :func:`neighbors.sort_graph_by_row_values` to sort a CSR sparse graph such that each row is stored with increasing values. This is useful to improve efficiency when using precomputed sparse distance matrices in a variety of estimators and avoid an EfficiencyWarning. :pr:`23139` by `Tom Dupre la Tour`_.

:mod:`sklearn.preprocessing`

• |Fix| :class:`preprocessing.PolynomialFeatures` with degree equal to 0 will raise error when include_bias is set to False, and outputs a single constant array when include_bias is set to True. :pr:`23370` by :user:`Zhehao Liu <MaxwellLZH>`.

:mod:`sklearn.tree`

• |Fix| Fixed invalid memory access bug during fit in :class:`tree.DecisionTreeRegressor` and :class:`tree.DecisionTreeClassifier`. :pr:`23273` by `Thomas Fan`_.

:mod:`sklearn.utils`

• |Enhancement| :func:`utils.extmath.randomized_svd` now accepts an argument, lapack_svd_driver, to specify the lapack driver used in the internal deterministic SVD used by the randomized SVD algorithm. :pr:`20617` by :user:`Srinath Kailasa <skailasa>`

Code and Documentation Contributors

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.1, including:

TODO: update at the time of the release.