DOC Add whats new info and update doc

Author: Guillaume Lemaitre

doc/api.rst

@@ -158,3 +158,20 @@ Functions
  :toctree: generated/
 
  datasets.make_imbalance
+
+
+Utilities
+=========
+
+.. automodule:: imblearn.utils
+ :no-members:
+ :no-inherited-members:
+
+.. currentmodule:: imblearn
+
+Functions
+---------
+.. autosummary::
+ :toctree: generated/
+
+ utils.estimators_checks.check_estimator

doc/whats_new.rst

@@ -41,6 +41,8 @@ Enhancement
 - Validate the type of target in binary samplers. A warning is raised for the moment. By `Guillaume Lemaitre`_ and `Christos Aridas`_.
 - Change from `cross_validation` module to `model_selection` module for
  `sklearn` deprecation cycle. By `Dayvid Oliveira`_ and `Christos Aridas`_.
+- All the unit tests have been factorized and a `check_estimators` has
+ been derived from scikit-learn. By `Guillaume Lemaitre`_.
 
 New features
 ~~~~~~~~~~~~
@@ -64,6 +66,8 @@ API changes summary
 - `k` has been deprecated in :class:`over_sampling.ADASYN`. Use `n_neighbors` instead. By `Guillaume Lemaitre`_.
 - `k` and `m` have been deprecated in :class:`over_sampling.SMOTE`. Use `k_neighbors` and `m_neighbors` instead. By `Guillaume Lemaitre`_.
 - `n_neighbors` accept `KNeighborsMixin` based object for :class:`under_sampling.EditedNearestNeighbors`, :class:`under_sampling.CondensedNeareastNeigbour`, :class:`under_sampling.NeighbourhoodCleaningRule`, :class:`under_sampling.RepeatedEditedNearestNeighbours`, and :class:`under_sampling.AllKNN`. By `Guillaume Lemaitre`_.
+- `__init__` has been removed from the :class:`base.SamplerMixin` to
+ create a real mixin class. By `Guillaume Lemaitre`_.
 
 Documentation changes
 ~~~~~~~~~~~~~~~~~~~~~

imblearn/__init__.py

@@ -17,6 +17,8 @@
  Module which provides methods to under-sample a dataset.
 under-sampling
  Module which provides methods to over-sample a dataset.
+utils
+ Module including various utilities.
 pipeline
  Module which allowing to create pipeline with scikit-learn estimators.
 """

imblearn/utils/estimators_checks.py

@@ -45,7 +45,8 @@ def _yield_all_checks(name, Estimator):
 
 
 def check_estimator(Estimator):
- """Check if estimator adheres to scikit-learn conventions and imblearn.
+ """Check if estimator adheres to scikit-learn conventions and
+ imbalanced-learn
 
  This estimator will run an extensive test-suite for input validation,
  shapes, etc.