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.
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.
Enhancement Introduce the new parameter
parser="pandas"allows to use the very CPU and memory efficient
pandas.read_csvparser 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 #21938 by Guillaume Lemaitre.
Feature Adds new function
neighbors.sort_graph_by_row_valuesto 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. #23139 by Tom Dupre la Tour.
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.