8000 FIX improve error message for large sparse matrix input in LogisticRe… · glemaitre/scikit-learn@454d931 · GitHub
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FIX improve error message for large sparse matrix input in LogisticRegression (scikit-learn#21093)
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doc/whats_new/v1.1.rst

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.. include:: _contributors.rst
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.. currentmodule:: sklearn
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.. _changes_1_1:
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Version 1.1.0
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=============
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**In Development**
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.. include:: changelog_legend.inc
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Minimal dependencies
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--------------------
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Version 1.1.0 of scikit-learn requires python 3.7+, numpy 1.14.6+ and
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scipy 1.1.0+. Optional minimal dependency is matplotlib 2.2.2+.
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Put the changes in their relevant module.
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Changed models
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--------------
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Changelog
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---------
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..
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Entries should be grouped by module (in alphabetic order) and prefixed with
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one of the labels: |MajorFeature|, |Feature|, |Efficiency|, |Enhancement|,
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|Fix| or |API| (see whats_new.rst for descriptions).
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Entries should be ordered by those labels (e.g. |Fix| after |Efficiency|).
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Changes not specific to a module should be listed under *Multiple Modules*
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or *Miscellaneous*.
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Entries should end with:
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:pr:`123456` by :user:`Joe Bloggs <joeongithub>`.
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where 123456 is the *pull request* number, not the issue number.
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:mod:`sklearn.linear_model`
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...........................
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- |Fix| :class:`linear_model.LogisticRegression` now raises a better error
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message when the solver does not support sparse matrices with int64 indices.
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:pr:`21093` by `Tom Dupre la Tour`_.
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:mod:`sklearn.utils`
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....................
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- |Enhancement| :func:`utils.validation._check_sample_weight` can perform a
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non-negativity check on the sample weights. It can be turned on
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using the only_non_negative bool parameter.
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Estimators that check for non-negative weights are updated:
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:func:`linear_model.LinearRegression` (here the previous
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error message was misleading),
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:func:`ensemble.AdaBoostClassifier`,
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:func:`ensemble.AdaBoostRegressor`,
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:func:`neighbors.KernelDensity`.
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:pr:`20880` by :user:`Guillaume Lemaitre <glemaitre>`
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and :user:`András Simon <simonandras>`.
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:mod:`sklearn.pipeline`
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.......................
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- |Enhancement| Added support for "passthrough" in :class:`FeatureUnion`.
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Setting a transformer to "passthrough" will pass the features unchanged.
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:pr:`20860` by :user:`Shubhraneel Pal <shubhraneel>`.
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Code and Documentation Contributors
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-----------------------------------
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Thanks to everyone who has contributed to the maintenance and improvement of
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the project since version 1.0, including:
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TODO: update at the time of the release.

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