* rm dupes
* add check_supervised_y_no_nan in classifier checks: this implies changes for Ridge classifiers
* fix docstrings/comments
* FIX check fitting 1d X array raises error and FIX check fitting 2d array with only 1 feature either works or returns informative message
* modify check_fit2d_1sample in common tests so that it checks fitting either works or returns an informative message
* rm SpectralClustering case for the moment
* uniformize error messages for 1 sample case and fix SpectralClustering with ensure_min_samples=2
* add unit test for mean_shift when n_samples * quantile < 1
* FIX travis with ensure_min_samples=2 in _PLS
* try fix for failing tSNE test
* typos
* take @agramfort's review into account
* sc to fix string in gaussian_process
* add the class that is present to preserve information of previous message in gpc.py
* some bug fixes.
* minor fixes to whatsnew
* typo in whatsnew
* add test for n_components = 1 transform in dict learning
* feature extraction doc fix
* fix broken test
* revert aggressive input validation changes
* in SelectFromModel, don't store threshold_ in transform. If we called "fit", use estimates from last "fit".
* move score from EllipticEnvelope to OutlierDetectionMixin
* revert changes to Tfidf documentation
* remove dummy input validation from whatsnew
* fix text feature tests
* rewrite from_model threshold again...
* remove stray condition
* fix self.estimator -> estimator, slightly more interesting test
* typo in comment
* Fix issues in SparseEncoder, add tests.
more explicit explanation of SparseEncoder change, add issue numbers to whatsnew
* minor fixes in whats_new.rst
* slightly more consistency with tuples for shapes
* not longer typo
* reintroduced isclose() and flake8 fixes to fixes.py
* changed == 0.0 to isclose(...)
* example changes
* changed back to abs() < epsilon
* flake8 convention on file
* reverted flake8 fixes
* reverted flake8 fixes (2)
* np.finfo(np.float32).tiny instead of hard coded epsilon 1e-150
* reverted to 1e-150
* whats new modified
ensure that estimators only add private attributes and attributes with
trailing _
in cases when existing estimators don't follow this new rule, we deprecate the
attributes and make them follow this rule
* remove stuff to be removed 0.19
* more changes
* remove classes from 0.19 whatsnew
* remove _LearntSelectorMixin
* remove ProjectedGradientNMF, load_lwf_*
* minor fixes
* remove more copy from logistic regression path
* remove lda, qda from __init__.__all__
* remove pg solver in nmf from tests etc
* remove class_weight="auto" from tests
* doctest change for decision_function_shape="ovr"
* remove transfrom from tree test, minor fixes to tree tests
* some fixes in the tests
* undo changes in functions which still allow 1d input...
* also allow 1d in scale
* more test fixes...
* last test fixes in forest and tree
* svm default value change doctest failures
* pep8
* remove more class_weight="auto" stuff
* minor cosmetics in docstrings deprecated / removed behavior.
* say that store_covariance has been moved to __init__ in discriminant_analysis
* fix min_weight_fraction_leaf when sample_weights is None
* fix flake8 error
* remove added newline and unnecessary assignment
* remove max bc it's implemented in cython and add interaction test
* edit weight calculation formula and add test to check equality
* remove test that sees if two parameter build the same tree
* reword min_weight_fraction_leaf docstring
* clarify uniform weight in forest docstrings
* update docstrings for all classes
* add what's new entry
* move whatsnew entry to bug fixes and explain previous behavior
* insert versionadded versionchanged directives in docstrings for 0.18
indicate where exception classes were moved from
* moved versionadded in the proper places
Rüdiger Busche
Hanmin Qin