diff --git a/doc/whats_new/v0.6.rst b/doc/whats_new/v0.6.rst index 852b71b28..d2b995501 100644 --- a/doc/whats_new/v0.6.rst +++ b/doc/whats_new/v0.6.rst @@ -39,6 +39,7 @@ scikit-learn: The following samplers will give different results due to change linked to the random state internal usage: +- :class:`imblearn.over_sampling.ADASYN` - :class:`imblearn.over_sampling.SMOTENC` Bug fixes @@ -100,13 +101,14 @@ Enhancement :pr:`644` by :user:`Guillaume Lemaitre `. - The samples generation in + :class:`imblearn.over_sampling.ADASYN`, :class:`imblearn.over_sampling.SMOTE`, :class:`imblearn.over_sampling.BorderlineSMOTE`, :class:`imblearn.over_sampling.SVMSMOTE`, :class:`imblearn.over_sampling.KMeansSMOTE`, :class:`imblearn.over_sampling.SMOTENC` is now vectorize with giving an additional speed-up when `X` in sparse. - :pr:`596` by :user:`Matt Eding `. + :pr:`596` and :pr:`649` by :user:`Matt Eding `. Deprecation ........... diff --git a/imblearn/ensemble/_forest.py b/imblearn/ensemble/_forest.py index f9417c649..3724abaa0 100644 --- a/imblearn/ensemble/_forest.py +++ b/imblearn/ensemble/_forest.py @@ -206,7 +206,7 @@ class BalancedRandomForestClassifier(RandomForestClassifier): subtree with the largest cost complexity that is smaller than ``ccp_alpha`` will be chosen. By default, no pruning is performed. - .. versionadded:: 0.22 + .. versionadded:: 0.6 Added in `scikit-learn` in 0.22 max_samples : int or float, default=None @@ -220,7 +220,7 @@ class BalancedRandomForestClassifier(RandomForestClassifier): the number of samples given in `max_samples` and the number of samples obtained after resampling. - .. versionadded:: 0.22 + .. versionadded:: 0.6 Added in `scikit-learn` in 0.22 Attributes