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Releases: scikit-learn-contrib/imbalanced-learn

0.4.0

12 Oct 15:27
10a658f
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Version 0.4

October, 2018

.. warning::

Version 0.4 is the last version of imbalanced-learn to support Python 2.7
and Python 3.4. Imbalanced-learn 0.5 will require Python 3.5 or higher.

Highlights

This release brings its set of new feature as well as some API changes to
strengthen the foundation of imbalanced-learn.

As new feature, 2 new modules imblearn.keras and
imblearn.tensorflow have been added in which imbalanced-learn samplers
can be used to generate balanced mini-batches.

The module imblearn.ensemble has been consolidated with new classifier:
imblearn.ensemble.BalancedRandomForestClassifier,
imblearn.ensemble.EasyEnsembleClassifier,
imblearn.ensemble.RUSBoostClassifier.

Support for string has been added in
imblearn.over_sampling.RandomOverSampler and
imblearn.under_sampling.RandomUnderSampler. In addition, a new class
imblearn.over_sampling.SMOTENC allows to generate sample with data
sets containing both continuous and categorical features.

The imblearn.over_sampling.SMOTE has been simplified and break down
to 2 additional classes:
imblearn.over_sampling.SVMSMOTE and
imblearn.over_sampling.BorderlineSMOTE.

There is also some changes regarding the API:
the parameter sampling_strategy has been introduced to replace the
ratio parameter. In addition, the return_indices argument has been
deprecated and all samplers will exposed a sample_indices_ whenever this is
possible.

0.3.4

07 Sep 13:56
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Just for switching documentation

0.3.3

22 Feb 13:50
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Bug fix in the classification report

0.3.2

07 Dec 23:01
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bumpversion 0.3.2

0.3.1

09 Oct 14:18
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Minor documentation revisions

0.3.0

09 Oct 13:39
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What's new in version 0.3.0

Testing

  • Pytest is used instead of nosetests. :issue:321 by Joan Massich_.

Documentation

  • Added a User Guide and extended some examples. :issue:295 by Guillaume Lemaitre_.

Bug fixes

  • Fixed a bug in :func:utils.check_ratio such that an error is raised when
    the number of samples required is negative. :issue:312 by Guillaume Lemaitre_.

  • Fixed a bug in :class:under_sampling.NearMiss version 3. The
    indices returned were wrong. :issue:312 by Guillaume Lemaitre_.

  • Fixed bug for :class:ensemble.BalanceCascade and :class:combine.SMOTEENN
    and :class:SMOTETomek. :issue:295 by Guillaume Lemaitre_.`

  • Fixed bug for check_ratio to be able to pass arguments when ratio is a
    callable. :issue:307 by Guillaume Lemaitre_.`

New features

  • Turn off steps in :class:pipeline.Pipeline using the None
    object. By Christos Aridas_.

  • Add a fetching function :func:datasets.fetch_datasets in order to get some
    imbalanced datasets useful for benchmarking. :issue:249 by Guillaume Lemaitre_.

Enhancement

  • All samplers accepts sparse matrices with defaulting on CSR type. :issue:316 by
    Guillaume Lemaitre_.

  • :func:datasets.make_imbalance take a ratio similarly to other samplers. It
    supports multiclass. :issue:312 by Guillaume Lemaitre_.

  • All the unit tests have been factorized and a :func:utils.check_estimators
    has been derived from scikit-learn. By Guillaume Lemaitre_.

  • Script for automatic build of conda packages and uploading. :issue:242 by
    Guillaume Lemaitre_

  • Remove seaborn dependence and improve the examples. :issue:264 by Guillaume Lemaitre_.

  • adapt all classes to multi-class resampling. :issue:290 by Guillaume Lemaitre_

API changes summary

  • __init__ has been removed from the :class:base.SamplerMixin to
    create a real mixin class. :issue:242 by Guillaume Lemaitre_.

  • creation of a module :mod:exceptions to handle consistant raising of
    errors. :issue:242 by Guillaume Lemaitre_.

  • creation of a module utils.validation to make checking of
    recurrent patterns. :issue:242 by Guillaume Lemaitre_.

  • move the under-sampling methods in prototype_selection and
    prototype_generation submodule to make a clearer dinstinction. :issue:277 by
    Guillaume Lemaitre_.

  • change ratio such that it can adapt to multiple class problems. :issue:290 by
    Guillaume Lemaitre_.

Deprecation

  • Deprecation of the use of min_c_ in :func:datasets.make_imbalance. :issue:312 by
    Guillaume Lemaitre_

  • Deprecation of the use of float in :func:datasets.make_imbalance for the
    ratio parameter. :issue:290 by Guillaume Lemaitre_.

  • deprecate the use of float as ratio in favor of dictionary, string, or
    callable. :issue:290 by Guillaume Lemaitre_.

0.2.1

01 Jan 15:44
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release 0.2.1

0.2.0

31 Dec 16:51
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Release 0.2.0

0.1.9

26 Dec 13:11
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release 0.1.9

0.1.8

07 Sep 12:50
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Solve issue #150 (#151)

* Solve issue #150

* Release 0.1.8