* More flexible grid search interface
* added info dict parameter
* Put back removed test
* renamed info into more_results
* Passed grroups as well since we need n_to use get_n_splits(X, y, groups)
* port
* pep8
* dabl -> sklearn
* add _required_parameters
* skipping check in rst file if pandas not installed
* Update sklearn/model_selection/_search_successive_halving.py
Co-Authored-By: Joel Nothman <joel.nothman@gmail.com>
* renamed into GridHalvingSearchCV and RandomHalvingSearchCV
* Addressed thomas' comments
* repr
* removed passing group as a parameter to evaluate_candidates
* Joels comments
* pep8
* reorganized user user guide
* renaming
* update user guide
* remove groups support + pass fit_params
* parameter renaming
* pep8
* r_i -> resource_iter
* fixed r_i issues
* examples + removed use of word budget
* Added inpute checking tests
* added cv_resutlts_ user guide
* minor title change
* fixed doc layout
* Addressed some comments
* properly pass down fit_params
* change default value of force_exhaust_resources and update doc
* should fix doc
* Used check_fit_params
* Update section about min_resources and number of candidates
* Clarified ratio section
* Use ~ to refer to classes
* fixed doc checks
* Apply suggestions from code review
Co-authored-by: Joel Nothman <joel.nothman@gmail.com>
* Addressed easy comments from Joel
* missed some
* updated docstring of run_search
* Used f strings instead of format
* remove candidate duplication checks
* fix example
* Addressed easy comments
* rotate ticks labels
* Added discussion in the intro as suggested by Joel
* Split examples into sections
* minor changes
* remove force_exhaust_budget and introduce min_resources=exhaust
* some minor validation
* Added a n_resources_ attribute
* update examples
* Addressed comments
* passing CV instead of X,y
* minor revert for handling fit_params
* updated docs
* fix len
* whatsnew
* Add test for sampling when all_list
* minor change to top-k
* Force CV splits to be consistent across calls
* reorder parameters
* reduced diff
* added tests for top_k
* put back doc for groups
* not sure what went wrong
* put import at its place
* some comment
* Addressed comments
* Added tests for cv_results_ and base estimator inputs
* pep8
* avoid monkeypatching
* rename df
* use Joel's suggestions for testing masks
* Made it experimental
* Should fix docs
* whats new entry
* Apply suggestions from code review
Co-authored-by: Andreas Mueller <t3kcit@gmail.com>
* Addressed comments to docs
* Addressed comments in examples
* minor doc update
* minor renaming in UG
* forgot some
* some sad note about splitter statefulness :'(
* Addressed comments
* ratio -> factor
Co-authored-by: Joel Nothman <joel.nothman@gmail.com>
Co-authored-by: Andreas Mueller <t3kcit@gmail.com>
* normalize_components in sparsePCA
* changed default strategy of Dummy to prior and removed outputs_2d ttribute
* removed usage of None to drop estimator in ensemble and behaviour param of IsolationForest
* remove support for drop=None in Voting
* removed some warning decorators
* remove feature_extraction.extract_patches
* removed VectorizerMixin and copy parameter from TFIDFVectorizer
* kernel.set_params now raises attributeerror
* removed fig from plot_partial_dependence
* removed iid parameter of search estimators
* removed brier_scorer
* raise error in split when shuffle is False and random_state is not None
* removed MultiOutputEstimator
* removed base classes of NaiveBayes
* removed drop from pipeline
* removed utils in random_projection
* removed presort and classes_ in trees
* flake8
* fixed some tests
* flake
* fixed docstring
* fixed other one
* some left
* mmmm
* Enable StratifiedKFold to produce different splits
* what's new
* redundant statement
* update what's new
* redundant comment
* add a test
* move what's new entry
* review comment
* review comment
* Fixed typo in an example
* Removed un-needed lines from example
* Added tests on the validity of parameters
* Fixed error msg for train_size issue
* Added tests to check the validation of test and train sizes
* Switched to parameterized test
* Fixed typo in error msg
* Swithced to pytest.raises
* Swithced to pytest.raises also when checking msg
* Improved the validity tests and their unit testing
Part of #11992.
These were all the things that seemed pretty straight-forward. It's actually a bit bulky but should still be easy to review, hopefully.
* add FutureWarning for methods with defaults=3
* add explicit cv values to fix assertion errors
* add tests for catching the FutureWarning
* Write current deprecation version
* Add deprecation in docstring
* change default cv value to None
* change cv from 3 to 5 in the examples
* upgrade doctests
* update doctest in tutorial
* update doctest in cross-validation doc
* fix tests
* add entry to whats new
* address Gael comments
* address Gael comments 2
* fix wrong indentation
* update doc
* add docstring deprecation warning in CV subclasses
* address Andy's comments
* fix PR number
* fix flake8
* add filterwarnings in tests
* fix doctests
* cv=None mendatory in Ridge
* fix warning related errors
* skip some doctests warnings
* make travis happy
* change from deprecated to versionchanged
* fix doctests and remove skipping
* address comments
* Use ' '.join(row) for multi-label targets in StratifiedShuffleSplit because str(row) uses an ellipsis when len(row) > 1000
* Add a new test for multilabel problems with more than a thousand labels
* DOC Add NOTE that unless random_state is set, split will not be identical
* TST use np.testing.assert_equal for nested lists/arrays
* TST Make sure cv param can be a generator
* DOC rank_ becomes a link when rendered
* Use test_...
* Remove blank line; Add if shuffle is True
* Fix tests
* Explicitly test for GeneratorType
* TST Add the else clause
* TST Add comment on usage of np.testing.assert_array_equal
* TYPO
* MNT Remove if ;
* Address Joel's comments
* merge the identical points in doc
* DOC address Andy's comments
* Move comment to before the check for generator type
* regression test and fix for 2d stratified shuffle split
* strengthen non-overlap sss tests
* clarify test and comment
* remove iter from tests, use str instead of hash
* add shuffle paramater to train_test_split
* fix syntax error
* fix variable name
* fix formatting in doctest output
* fix doctest output
* refactor shuffle paramater into ShuffleSplit and StratifiedShuffleSplit
* include shuffle option in tests
* rollback refactor
* revert to simpler version of unshuffled split
* fix flake8 errors
* revert changes to ShuffleSplit
* revert BaseShuffleSplit
* more reversions
* fix indentation
* remove shuffle parameter from CVclass
* add text to NotImplementedError
* change indexing to use numpy.arange rather than range
* specify precondition for stratify to be None in docstring
Nicolas Hug
Hanmin Qin