* 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>
Co-authored-by: Cary Goltermann <cgoltermann@kpmg.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: rasbt <mail@sebastianraschka.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
* Add Tensor Sketch algorithm
* Add user guide entry
* Add example
* Add benchmark
Co-authored-by: Christian Lorentzen <lorentzen.ch@googlemail.com>
Co-authored-by: Tom Dupré la Tour <tom.dupre-la-tour@m4x.org>
Co-authored-by: Roman Yurchak <rth.yurchak@gmail.com>
* fix error tuple passed to order
* fix linting
* Update sklearn/tests/test_multioutput.py
Co-authored-by: Roman Yurchak <rth.yurchak@gmail.com>
* updated test and whatsnew
* doc fix
* Update doc/whats_new/v0.24.rst
Co-authored-by: Roman Yurchak <rth.yurchak@gmail.com>
* Update sklearn/tests/test_multioutput.py
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
* Update sklearn/tests/test_multioutput.py
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
* code review fix
* code review fix
* added test
* code review fix
* Update sklearn/multioutput.py
Co-authored-by: Joel Nothman <joel.nothman@gmail.com>
Co-authored-by: Roman Yurchak <rth.yurchak@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Joel Nothman <joel.nothman@gmail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Thomas J Fan <thomasjpfan@gmail.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
* fix: Reduce warnings for k_means and discriminant_analysis
- Reduce the number of warnings for k_means by setting n_init to 1
when proviging initialization centers
- Remove discriminant_analysis test warnings by guarding against zero
division for `predict_log_proba`
- Print `p` parameter ignore warning only when different than `None`
* add tests for warning case
* fix lint issues
* address warnings
* fix linting
* 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
Olivier Grisel