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api.rst

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imbalanced-learn API

This is the full API documentation of the imbalanced-learn toolbox.

:mod:`imblearn.under_sampling`: Under-sampling methods

.. automodule:: imblearn.under_sampling
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

Prototype generation

.. automodule:: imblearn.under_sampling.prototype_generation
   :no-members:
   :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   under_sampling.ClusterCentroids

Prototype selection

.. automodule:: imblearn.under_sampling.prototype_selection
   :no-members:
   :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   under_sampling.CondensedNearestNeighbour
   under_sampling.EditedNearestNeighbours
   under_sampling.RepeatedEditedNearestNeighbours
   under_sampling.AllKNN
   under_sampling.InstanceHardnessThreshold
   under_sampling.NearMiss
   under_sampling.NeighbourhoodCleaningRule
   under_sampling.OneSidedSelection
   under_sampling.RandomUnderSampler
   under_sampling.TomekLinks

:mod:`imblearn.over_sampling`: Over-sampling methods

.. automodule:: imblearn.over_sampling
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   over_sampling.ADASYN
   over_sampling.RandomOverSampler
   over_sampling.SMOTE


:mod:`imblearn.combine`: Combination of over- and under-sampling methods

.. automodule:: imblearn.combine
   :no-members:
   :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   combine.SMOTEENN
   combine.SMOTETomek

:mod:`imblearn.ensemble`: Ensemble methods

.. automodule:: imblearn.ensemble
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   ensemble.BalanceCascade
   ensemble.BalancedBaggingClassifier
   ensemble.EasyEnsemble

Miscellaneous

Imbalance-learn provides some fast-prototyping tools.

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   FunctionSampler

.. automodule:: imblearn.pipeline
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: class.rst

   pipeline.Pipeline

.. autosummary::
   :toctree: generated/
   :template: function.rst

   pipeline.make_pipeline

.. automodule:: imblearn.metrics
   :no-members:
   :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: function.rst

   metrics.classification_report_imbalanced
   metrics.sensitivity_specificity_support
   metrics.sensitivity_score
   metrics.specificity_score
   metrics.geometric_mean_score
   metrics.make_index_balanced_accuracy

.. automodule:: imblearn.datasets
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: function.rst

   datasets.make_imbalance
   datasets.fetch_datasets

.. automodule:: imblearn.utils
    :no-members:
    :no-inherited-members:

.. currentmodule:: imblearn

.. autosummary::
   :toctree: generated/
   :template: function.rst

   utils.estimator_checks.check_estimator
   utils.check_neighbors_object
   utils.check_ratio
   utils.check_sampling_strategy
   utils.hash_X_y