# Version 1.3.0¶

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.

## 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.

## Changes impacting all modules¶

• Enhancement The get_feature_names_out method of the following classes now raises a NotFittedError if the instance is not fitted. This ensures the error is consistent in all estimators with the get_feature_names_out method.

The NotFittedError displays an informative message asking to fit the instance with the appropriate arguments.

## Changelog¶

### sklearn.exception¶

• Feature Added exception.InconsistentVersionWarning which is raised when a scikit-learn estimator is unpickled with a scikit-learn version that is inconsistent with the sckit-learn verion the estimator was pickled with. #25297 by Thomas Fan.

### sklearn.utils¶

• API Change estimator_checks.check_transformers_unfitted_stateless has been introduced to ensure stateless transformers don’t raise NotFittedError during transform with no prior call to fit or fit_transform. #25190 by Vincent Maladière.

## Code and Documentation Contributors¶

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.2, including:

TODO: update at the time of the release.