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@glemaitre glemaitre released this 05 Dec 14:24
· 8 commits to 0.6.X since this release
0.6.0
3025283

Changelog

Changed models
..............

The following models might give some different sampling due to changes in
scikit-learn:

  • :class:imblearn.under_sampling.ClusterCentroids
  • :class:imblearn.under_sampling.InstanceHardnessThreshold

The following samplers will give different results due to change linked to
the random state internal usage:

  • :class:imblearn.over_sampling.SMOTENC

Bug fixes
.........

  • :class:imblearn.under_sampling.InstanceHardnessThreshold now take into
    account the random_state and will give deterministic results. In addition,
    cross_val_predict is used to take advantage of the parallelism.
    :pr:599 by :user:Shihab Shahriar Khan <Shihab-Shahriar>.

  • Fix a bug in :class:imblearn.ensemble.BalancedRandomForestClassifier
    leading to a wrong computation of the OOB score.
    :pr:656 by :user:Guillaume Lemaitre <glemaitre>.

Maintenance
...........

  • Update imports from scikit-learn after that some modules have been privatize.
    The following import have been changed:
    :class:sklearn.ensemble._base._set_random_states,
    :class:sklearn.ensemble._forest._parallel_build_trees,
    :class:sklearn.metrics._classification._check_targets,
    :class:sklearn.metrics._classification._prf_divide,
    :class:sklearn.utils.Bunch,
    :class:sklearn.utils._safe_indexing,
    :class:sklearn.utils._testing.assert_allclose,
    :class:sklearn.utils._testing.assert_array_equal,
    :class:sklearn.utils._testing.SkipTest.
    :pr:617 by :user:Guillaume Lemaitre <glemaitre>.

  • Synchronize :mod:imblearn.pipeline with :mod:sklearn.pipeline.
    :pr:620 by :user:Guillaume Lemaitre <glemaitre>.

  • Synchronize :class:imblearn.ensemble.BalancedRandomForestClassifier and add
    parameters max_samples and ccp_alpha.
    :pr:621 by :user:Guillaume Lemaitre <glemaitre>.

Enhancement
...........

  • :class:imblearn.under_sampling.RandomUnderSampling,
    :class:imblearn.over_sampling.RandomOverSampling,
    :class:imblearn.datasets.make_imbalance accepts Pandas DataFrame in and
    will output Pandas DataFrame. Similarly, it will accepts Pandas Series in and
    will output Pandas Series.
    :pr:636 by :user:Guillaume Lemaitre <glemaitre>.

  • :class:imblearn.FunctionSampler accepts a parameter validate allowing
    to check or not the input X and y.
    :pr:637 by :user:Guillaume Lemaitre <glemaitre>.

  • :class:imblearn.under_sampling.RandomUnderSampler,
    :class:imblearn.over_sampling.RandomOverSampler can resample when non
    finite values are present in X.
    :pr:643 by :user:Guillaume Lemaitre <glemaitre>.

  • All samplers will output a Pandas DataFrame if a Pandas DataFrame was given
    as an input.
    :pr:644 by :user:Guillaume Lemaitre <glemaitre>.

  • The samples generation in
    :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 <MattEding>.

Deprecation
...........

  • The following classes have been removed after 2 deprecation cycles:
    ensemble.BalanceCascade and ensemble.EasyEnsemble.
    :pr:617 by :user:Guillaume Lemaitre <glemaitre>.

  • The following functions have been removed after 2 deprecation cycles:
    utils.check_ratio.
    :pr:617 by :user:Guillaume Lemaitre <glemaitre>.

  • The parameter ratio and return_indices has been removed from all
    samplers.
    :pr:617 by :user:Guillaume Lemaitre <glemaitre>.

  • The parameters m_neighbors, out_step, kind, svm_estimator
    have been removed from the :class:imblearn.over_sampling.SMOTE.
    :pr:617 by :user:Guillaume Lemaitre <glemaitre>.

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