Version 1.0.0

In Development

Legend for changelogs

  • Major Feature : something big that you couldn’t do before.

  • Feature : something that you couldn’t do before.

  • Efficiency : an existing feature now may not require as much computation or memory.

  • Enhancement : a miscellaneous minor improvement.

  • Fix : something that previously didn’t work as documentated – or according to reasonable expectations – should now work.

  • API Change : you will need to change your code to have the same effect in the future; or a feature will be removed in the future.

Put the changes in their relevant module.

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.

Details are listed in the changelog below.

(While we are trying to better inform users by providing this information, we cannot assure that this list is complete.)

Changelog

sklearn.cluster

sklearn.feature_extraction

  • Fix Fixed a bug in class:feature_extraction.HashingVectorizer where some input strings would result in negative indices in the transformed data. #19035 by Liu Yu.

sklearn.linear_model

  • Enhancement Validate user-supplied gram matrix passed to linear models via the precompute argument. #19004 by Adam Midvidy.

  • Fix ElasticNet.fit no longer modifies sample_weight in place. #19055 by Thomas Fan.

  • Fix Lasso, ElasticNet no longer have a dual_gap_ not corresponding to their objective. #19172 by Mathurin Massias

  • API Change : The parameter normalize of linear_model.LinearRegression is deprecated and will be removed in 1.2. Motivation for this deprecation: normalize parameter did not take any effect if fit_intercept was set to False and therefore was deemed confusing. The behavior of the deprecated LinearRegression(normalize=True) can be reproduced with Pipeline with :pr:`17743 by Maria Telenczuk and Alexandre Gramfort.

sklearn.metrics

sklearn.naive_bayes

sklearn.preprocessing

sklearn.tree

Code and Documentation Contributors

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 0.24, including:

TODO: update at the time of the release.