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bumpversion to 0.8.0.dev0
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doc/whats_new.rst

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Release history
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===============
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.. include:: whats_new/v0.8.rst
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.. include:: whats_new/v0.7.rst
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.. include:: whats_new/v0.6.rst

doc/whats_new/v0.7.rst

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:class:`imblearn.over_sampling.SMOTENC`.
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:pr:`675` by :user:`bganglia <bganglia>`.
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- Fix a bug in :class:`imblearn.under_sampling.ClusterCentroids` where
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`voting="hard"` could have lead to select a sample from any class instead of
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the targeted class.
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:pr:`769` by :user:`Guillaume Lemaitre <glemaitre>`.
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- Fix a bug in :class:`imblearn.FunctionSampler` where validation was performed
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even with `validate=False` when calling `fit`.
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:pr:`790` by :user:`Guillaume Lemaitre <glemaitre>`.
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Enhancements
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............
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- Lazy import `keras` module when importing `imblearn.keras`
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:pr:`719` by :user:`Guillaume Lemaitre <glemaitre>`.
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- Added an option to generate smoothed bootstrap in
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:class:`imblearn.over_sampling.RandomOverSampler`. It is controls by the
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parameter `shrinkage`. This method is also known as Random Over-Sampling
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Examples (ROSE).
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:pr:`754` by :user:`Andrea Lorenzon <andrealorenzon>` and
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:user:`Guillaume Lemaitre <glemaitre>`.
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- Add option `output_dict` in
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:func:`imblearn.metrics.classification_report_imbalanced` to return a
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dictionary instead of a string.
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:pr:`770` by :user:`Guillaume Lemaitre <glemaitre>`.
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- Add the the function
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:func:`imblearn.metrics.macro_averaged_mean_absolute_error` returning the
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average across class of the MAE. This metric is used in ordinal
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classification.
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:pr:`780` by :user:`Aurélien Massiot <AurelienMassiot>`.
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Deprecation
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...........
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doc/whats_new/v0.8.rst

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.. _changes_0_8:
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Version 0.8.0 (Under development)
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=================================
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Changelog
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---------
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New features
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............
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- Add the the function
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:func:`imblearn.metrics.macro_averaged_mean_absolute_error` returning the
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average across class of the MAE. This metric is used in ordinal
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classification.
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:pr:`780` by :user:`Aurélien Massiot <AurelienMassiot>`.
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Enhancements
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............
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- Add option `output_dict` in
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:func:`imblearn.metrics.classification_report_imbalanced` to return a
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dictionary instead of a string.
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:pr:`770` by :user:`Guillaume Lemaitre <glemaitre>`.
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- Added an option to generate smoothed bootstrap in
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:class:`imblearn.over_sampling.RandomOverSampler`. It is controls by the
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parameter `shrinkage`. This method is also known as Random Over-Sampling
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Examples (ROSE).
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:pr:`754` by :user:`Andrea Lorenzon <andrealorenzon>` and
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:user:`Guillaume Lemaitre <glemaitre>`.
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Bug fixes
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.........
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- Fix a bug in :class:`imblearn.under_sampling.ClusterCentroids` where
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`voting="hard"` could have lead to select a sample from any class instead of
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the targeted class.
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:pr:`769` by :user:`Guillaume Lemaitre <glemaitre>`.
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- Fix a bug in :class:`imblearn.FunctionSampler` where validation was performed
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even with `validate=False` when calling `fit`.
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:pr:`790` by :user:`Guillaume Lemaitre <glemaitre>`.

imblearn/_version.py

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# 'X.Y.dev0' is the canonical version of 'X.Y.dev'
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#
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__version__ = "0.7.0"
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__version__ = "0.8.0.dev0"

setup.cfg

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[bumpversion]
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current_version = 0.7.0
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current_version = 0.8.0.dev0
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tag = False
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parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\.(?P<release>[a-z]+)(?P<dev>\d+))?
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serialize =
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[flake8]
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max-line-length = 88
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# Default flake8 3.5 ignored flags
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ignore=E121,E123,E126,E226,E24,E704,W503,W504,E203
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# It's fine not to put the import at the top of the file in the examples
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# folder.
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ignore = E121,E123,E126,E226,E24,E704,W503,W504,E203
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per-file-ignores =
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examples/*: E402
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examples/*: E402

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