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.
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.)
API Change : The parameter
linear_model.LinearRegressionis deprecated and will be removed in 1.2. Motivation for this deprecation:
normalizeparameter did not take any effect if
fit_interceptwas set to False and therefore was deemed confusing. The behavior of the deprecated LinearRegression(normalize=True) can be reproduced with
:pr:`17743by Maria Telenczuk and Alexandre Gramfort.
metrics.ConfusionMatrixDisplayexposes two class methods
from_predictionsallowing to create a confusion matrix plot using an estimator or the predictions.
metrics.plot_confusion_matrixis deprecated in favor of these two class methods and will be removed in 1.2. #18543 by Guillaume Lemaitre.
partial_fitmethods of the discrete naive Bayes classifiers (
naive_bayes.MultinomialNB) now correctly handle the degenerate case of a single class in the training set. #18925 by David Poznik.
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.