[MRG] Fix documentation of default values in tree classes #15870
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NicolasHug
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Dec 12, 2019
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Thanks @alfaro96 !
Made a bunch of minor comments but this looks good
sklearn/tree/_classes.py
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| This parameter is deprecated and will be removed in v0.24. | ||
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| .. deprecated:: 0.22 | ||
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| ccp_alpha : non-negative float, optional (default=0.0) | ||
| ccp_alpha : positive float, default=0.0 |
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keep non-negative.
It's clearer that it can be 0
sklearn/tree/_classes.py
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| @@ -95,7 +95,7 @@ def __init__(self, | |||
| min_impurity_decrease, | |||
| min_impurity_split, | |||
| class_weight=None, | |||
| presort='deprecated', | |||
| presort="deprecated", | |||
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let's avoid that kind of stylistic change
sklearn/tree/_classes.py
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| @@ -589,21 +588,21 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): | |||
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| Parameters | |||
| ---------- | |||
| criterion : str, optional (default="gini") | |||
| criterion : str, default="gini" | |||
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when there are only a few alternatives we use:
Suggested change
| criterion : str, default="gini" | |
| criterion : {'gini', 'entropy'}, default="gini" |
sklearn/tree/_classes.py
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| The function to measure the quality of a split. Supported criteria are | ||
| "gini" for the Gini impurity and "entropy" for the information gain. | ||
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| splitter : str, optional (default="best") | ||
| splitter : str, default="best" |
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same
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| splitter : str, default="best" | |
| splitter : {'best', 'random'}, default="best" |
| The input samples. Internally, it will be converted to | ||
| ``dtype=np.float32`` and if a sparse matrix is provided | ||
| to a sparse ``csr_matrix``. | ||
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| check_input : bool | ||
| check_input : bool, default=True |
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also keep the description as above?
sklearn/tree/_classes.py
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| The input samples. Internally, it will be converted to | ||
| ``dtype=np.float32`` and if a sparse matrix is provided | ||
| to a sparse ``csr_matrix``. | ||
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| Returns | ||
| ------- | ||
| proba : array of shape (n_samples, n_classes), or a list of n_outputs \ | ||
| such arrays if n_outputs > 1. | ||
| proba : ndarray of shape (n_samples, n_classes) or list of int |
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it's not a list of int it's a list ndarrays where the list is of size n_outputs, I'd keep the original description
sklearn/tree/_classes.py
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| @@ -963,7 +957,7 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): | |||
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| Parameters | |||
| ---------- | |||
| criterion : str, optional (default="mse") | |||
| criterion : str, default="mse" | |||
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same suggestion as above, and same for the rest ;)
sklearn/tree/_classes.py
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| @@ -1380,7 +1375,7 @@ class ExtraTreeClassifier(DecisionTreeClassifier): | |||
| Note that these weights will be multiplied with sample_weight (passed | |||
| through the fit method) if sample_weight is specified. | |||
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| ccp_alpha : non-negative float, optional (default=0.0) | |||
| ccp_alpha : positive float, default=0.0 | |||
sklearn/tree/_classes.py
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| Grow a tree with ``max_leaf_nodes`` in best-first fashion. | ||
| Best nodes are defined as relative reduction in impurity. | ||
| If None then unlimited number of leaf nodes. | ||
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| ccp_alpha : non-negative float, optional (default=0.0) | ||
| ccp_alpha : positive float, default=0.0 |
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Thanks @NicolasHug for the comments! I will update these issues. |
thomasjpfan
reviewed
Dec 12, 2019
sklearn/tree/_classes.py
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| indicator : sparse csr array, shape = [n_samples, n_nodes] | ||
| Return a node indicator matrix where non zero elements | ||
| indicator : sparse matrix of shape (n_samples, n_nodes) | ||
| Return a node indicator matrix (csr) where non zero elements |
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Nit: I would prefer using CSR as an adjective:
Return a node indicator CSR matrix ..
sklearn/tree/_classes.py
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| Grow a tree with ``max_leaf_nodes`` in best-first fashion. | ||
| Best nodes are defined as relative reduction in impurity. | ||
| If None then unlimited number of leaf nodes. | ||
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| min_impurity_decrease : float, optional (default=0.) | ||
| min_impurity_decrease : float, default=0. |
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Nit:
Suggested change
| min_impurity_decrease : float, default=0. | |
| min_impurity_decrease : float, default=0.0 |
sklearn/tree/_classes.py
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| @@ -1011,12 +1008,12 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): | |||
| .. versionchanged:: 0.18 | |||
| Added float values for fractions. | |||
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| min_weight_fraction_leaf : float, optional (default=0.) | |||
| min_weight_fraction_leaf : float, default=0. | |||
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Nit:
Suggested change
| min_weight_fraction_leaf : float, default=0. | |
| min_weight_fraction_leaf : float, default=0.0 |
sklearn/tree/_classes.py
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| Grow a tree with ``max_leaf_nodes`` in best-first fashion. | ||
| Best nodes are defined as relative reduction in impurity. | ||
| If None then unlimited number of leaf nodes. | ||
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| min_impurity_decrease : float, optional (default=0.) | ||
| min_impurity_decrease : float, default=0. |
There was a problem hiding this comment.
Nit
Suggested change
| min_impurity_decrease : float, default=0. | |
| min_impurity_decrease : float, default=0.0 |
sklearn/tree/_classes.py
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| @@ -1299,12 +1297,12 @@ class ExtraTreeClassifier(DecisionTreeClassifier): | |||
| .. versionchanged:: 0.18 | |||
| Added float values for fractions. | |||
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| min_weight_fraction_leaf : float, optional (default=0.) | |||
| min_weight_fraction_leaf : float, default=0. | |||
There was a problem hiding this comment.
Nit:
Suggested change
| min_weight_fraction_leaf : float, default=0. | |
| min_weight_fraction_leaf : float, default=0.0 |
sklearn/tree/_classes.py
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| Grow a tree with ``max_leaf_nodes`` in best-first fashion. | ||
| Best nodes are defined as relative reduction in impurity. | ||
| If None then unlimited number of leaf nodes. | ||
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| min_impurity_decrease : float, optional (default=0.) | ||
| min_impurity_decrease : float, default=0. |
There was a problem hiding this comment.
Nit:
Suggested change
| min_impurity_decrease : float, default=0. | |
| min_impurity_decrease : float, default=0.0 |
sklearn/tree/_classes.py
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| @@ -1528,12 +1527,12 @@ class ExtraTreeRegressor(DecisionTreeRegressor): | |||
| .. versionchanged:: 0.18 | |||
| Added float values for fractions. | |||
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| min_weight_fraction_leaf : float, optional (default=0.) | |||
| min_weight_fraction_leaf : float, default=0. | |||
There was a problem hiding this comment.
Nit:
Suggested change
| min_weight_fraction_leaf : float, default=0. | |
| min_weight_fraction_leaf : float, default=0.0 |
sklearn/tree/_classes.py
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| If int, random_state is the seed used by the random number generator; | ||
| If RandomState instance, random_state is the random number generator; | ||
| If None, the random number generator is the RandomState instance used | ||
| by `np.random`. | ||
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| min_impurity_decrease : float, optional (default=0.) | ||
| min_impurity_decrease : float, default=0. |
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Nit:
Suggested change
| min_impurity_decrease : float, default=0. | |
| min_impurity_decrease : float, default=0.0 |
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@NicolasHug @thomasjpfan Done! You comments are very helpful, thanks! |
thomasjpfan
approved these changes
Dec 12, 2019
sklearn/tree/_classes.py
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| Allow to bypass several input checking. | ||
| Don't use this parameter unless you know what you do. | ||
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| X_idx_sorted : array-like of shape (n_samples, n_features), optional | ||
| X_idx_sorted : array-like of shape (n_samples, n_features), \ | ||
| default=None |
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Nit: @alfaro96 This was not addressed yet.
NicolasHug
approved these changes
Dec 12, 2019
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@NicolasHug @thomasjpfan: Fixed! |
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Thank you @alfaro96 ! |
ogrisel
reviewed
Dec 31, 2019
| 'values are "auto", "sqrt" or "log2".') | ||
| raise ValueError("Invalid value for max_features. " | ||
| "Allowed string values are 'auto', " | ||
| "'sqrt' or 'log2'.") |
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@alfaro96 as a side note, please do not include such unrelated stylistic changes in your PRs, it makes them more likely to cause conflicts when dealing with back ports for maintenance branches. Better keep the PR focused on the issue of the description.
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* DOC fixed default values in dbscan (#15753) * DOC fix incorrect branch reference in contributing doc (#15779) * DOC relabel Feature -> Efficiency in change log (#15770) * DOC fixed Birch default value (#15780) * STY Minior change on code padding in website theme (#15768) * DOC Fix yticklabels order in permutation importances example (#15799) * Fix yticklabels order in permutation importances example * STY Update wrapper width (#15793) * DOC Long sentence was hard to parse and ambiguous in _classification.py (#15769) * DOC Removed duplicate 'classes_' attribute in Naive Bayes classifiers (#15811) * BUG Fixes pandas dataframe bug with boolean dtypes (#15797) * BUG Returns only public estimators in all_estimators (#15380) * DOC improve doc for multiclass and types_of_target (#15333) * TST Increases tol for check_pca_float_dtype_preservation assertion (#15775) * update _alpha_grid class in _coordinate_descent.py (#15835) * FIX Explicit conversion of ndarray to object dtype. (#15832) * BLD Parallelize sphinx builds on circle ci (#15745) * DOC correct url for preprocessing (#15853) * MNT avoid generating too many cross links in examples (#15844) * DOC Correct wrong doc in precision_recall_fscore_support (#15833) * DOC add comment in check_pca_float_dtype_preservation (#15819) Documenting the changes in #15775 * DOC correct indents in docstring _split.py (#15843) * DOC fix docstring of KMeans based on sklearn guideline (#15754) * DOC fix docstring of AgglomerativeClustering based on sklearn guideline (#15764) * DOC fix docstring of AffinityPropagation based on sklearn guideline (#15777) * DOC fixed SpectralCoclustering and SpectralBiclustering docstrings following sklearn guideline (#15778) * DOC fix FeatureAgglomeration and MiniBatchKMeans docstring following sklearn guideline (#15809) * TST Specify random_state in test_cv_iterable_wrapper (#15829) * DOC Include LinearSV{C, R} in models that support sample_weights (#15871) * DOC correct some indents (#15875) * DOC Fix documentation of default values in tree classes (#15870) * DOC fix typo in docstring (#15887) * DOC FIX default value for xticks_rotation in plot_confusion_matrix (#15890) * Fix imports in pip3 ubuntu by suffixing affected files (#15891) * MNT Raise erorr when normalize is invalid in confusion_matrix (#15888) * [MRG] DOC Increases search results for API object results (#15574) * MNT Ignores warning in pyamg for deprecated scipy.random (#15914) * DOC Instructions to troubleshoot Windows path length limit (#15916) * DOC add versionadded directive to some estimators (#15849) * DOC clarify doc-string of roc_auc_score and add references (#15293) * MNT Adds skip lint to azure pipeline CI (#15904) * BLD Fixes bug when building with NO_MATHJAX=1 (#15892) * [MRG] BUG Checks to number of axes in passed in ax more generically (#15760) * EXA Minor fixes in plot_sparse_logistic_regression_20newsgroups.py (#15925) * BUG Do not shadow public functions with deprecated modules (#15846) * Import sklearn._distributor_init first (#15929) * DOC Fix typos, via a Levenshtein-style corrector (#15923) * DOC in canned comment, mention that PR title becomes commit me… (#15935) * DOC/EXA Correct spelling of "Classification" (#15938) * BUG fix pip3 ubuntu update by suffixing file (#15928) * [MRG] Ways to compute center_shift_total were different in "full" and "elkan" algorithms. (#15930) * TST Fixes integer test for train and test indices (#15941) * BUG ensure that parallel/sequential give the same permutation importances (#15933) * Formatting fixes in changelog (#15944) * MRG FIX: order of values of self.quantiles_ in QuantileTransformer (#15751) * [MRG] BUG Fixes constrast in plot_confusion_matrix (#15936) * BUG use zero_division argument in classification_report (#15879) * DOC change logreg solver in plot_logistic_path (#15927) * DOC fix whats new ordering (#15961) * COSMIT use np.iinfo to define the max int32 (#15960) * DOC Apply numpydoc validation to VotingRegressor methods (#15969) Co-authored-by: Tiffany R. Williams <Tiffany8@users.noreply.github.com> * DOC improve naive_bayes.py documentation (#15943) Co-authored-by: Jigna Panchal <40188288+jigna-panchal@users.noreply.github.com> * DOC Fix default values in Perceptron documentation (#15965) * DOC Improve default values in logistic documentation (#15966) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * DOC Improve documentation of default values for imputers (#15964) * EXA/MAINT Simplify code in manifold learning example (#15949) * DOC Improve default values in SGD documentation (#15967) * DOC Improve defaults in neural network documentation (#15968) * FIX use safe_sparse_dot for callable kernel in LabelSpreading (#15868) * BUG Adds attributes back to check_is_fitted (#15947) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * DOC update check_is_fitted what's new * DOC change python-devel to python3-devel for yum. (#15986) * DOC Correct the default value of values_format in plot_confusion_matrix (#15981) * [MRG] MNT Updates pypy to use 7.2.0 (#15954) * FIX Add missing 'values_format' param to disp.plot() in plot_confusion_matrix (#15937) * FIX support scalar values in fit_params in SearchCV (#15863) * support a scalar fit param * pep8 * TST add test for desired behavior * FIX introduce _check_fit_params to validate parameters * DOC update whats new * TST tests both grid-search and randomize-search * PEP8 * DOC revert unecessary change * TST add test for _check_fit_params * olivier comments * TST fixes * DOC whats new * DOC whats new * TST revert type of error * add olivier suggestions * address olivier comments * address thomas comments * PEP8 * comments olivier * TST fix test by passing X * avoid to call twice tocsr * add case column/row sparse in check_fit_param * provide optional indices * TST check content when indexing params * PEP8 * TST update tests to check identity * stupid fix * use a distribution in RandomizedSearchCV * MNT add lightgbm to one of the CI build * move to another build * do not install dependencies lightgbm * MNT comments on the CI setup * address some comments * Test fit_params compat without dependency on lightgbm Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * Remove abstractmethod that silently brake downstream packages (#15996) * FIX restore BaseNB._check_X without abstractmethod decoration (#15997) * Update v0.22 changelog for 0.22.1 (#16002) - set the date - move entry for quantile transformer to the 0.22.1 section - fix alphabetical ordering of modules * STY Removes hidden scroll bar (#15999) * Flake8 fixes * Fix: remove left-over lines that should have been deleted during conflict resolution when rebasing * Fix missing imports * Update version * Fix test_check_is_fitted * Make test_sag_regressor_computed_correctly deterministic (#16003) Fix #15818. Co-authored-by: cgsavard <claire.savard@colorado.edu> Co-authored-by: Joel Nothman <joel.nothman@gmail.com> Co-authored-by: Thomas J Fan <thomasjpfan@gmail.com> Co-authored-by: Matt Hall <matt@agilegeoscience.com> Co-authored-by: Kathryn Poole <kathryn.poole2@gmail.com> Co-authored-by: lucyleeow <jliu176@gmail.com> Co-authored-by: JJmistry <jayminm22@gmail.com> Co-authored-by: Juan Carlos Alfaro Jiménez <JuanCarlos.Alfaro@uclm.es> Co-authored-by: SylvainLan <sylvain.s.lannuzel@gmail.com> Co-authored-by: Nicolas Hug <contact@nicolas-hug.com> Co-authored-by: Hanmin Qin <qinhanmin2005@sina.com> Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> Co-authored-by: Vachan D A <vachanda@users.noreply.github.com> Co-authored-by: Sambhav Kothari <sambhavs.email@gmail.com> Co-authored-by: wenliwyan <12013376+wenliwyan@users.noreply.github.com> Co-authored-by: shivamgargsya <shivam.gargshya@gmail.com> Co-authored-by: Reshama Shaikh <rs2715@stern.nyu.edu> Co-authored-by: Oliver Urs Lenz <oulenz@users.noreply.github.com> Co-authored-by: Loïc Estève <loic.esteve@ymail.com> Co-authored-by: Brian Wignall <BrianWignall@gmail.com> Co-authored-by: Ritchie Ng <ritchieng@u.nus.edu> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: inderjeet <43402782+inder128@users.noreply.github.com> Co-authored-by: scibol <scibol@users.noreply.github.com> Co-authored-by: Tirth Patel <tirthasheshpatel@gmail.com> Co-authored-by: Bibhash Chandra Mitra <bibhashm220896@gmail.com> Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org> Co-authored-by: Tiffany R. Williams <Tiffany8@users.noreply.github.com> Co-authored-by: Jigna Panchal <40188288+jigna-panchal@users.noreply.github.com> Co-authored-by: @nkish <19225359+ankishb@users.noreply.github.com> Co-authored-by: Pulkit Mehta <pulkit_mehta_work@yahoo.com> Co-authored-by: David Breuer <DavidBreuer@users.noreply.github.com> Co-authored-by: Niklas <niklas.sm+github@gmail.com> Co-authored-by: Windber <guolipengyeah@126.com> Co-authored-by: Stephen Blystone <29995339+blynotes@users.noreply.github.com> Co-authored-by: Brigitta Sipőcz <b.sipocz@gmail.com>
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* DOC fixed default values in dbscan (scikit-learn#15753) * DOC fix incorrect branch reference in contributing doc (scikit-learn#15779) * DOC relabel Feature -> Efficiency in change log (scikit-learn#15770) * DOC fixed Birch default value (scikit-learn#15780) * STY Minior change on code padding in website theme (scikit-learn#15768) * DOC Fix yticklabels order in permutation importances example (scikit-learn#15799) * Fix yticklabels order in permutation importances example * STY Update wrapper width (scikit-learn#15793) * DOC Long sentence was hard to parse and ambiguous in _classification.py (scikit-learn#15769) * DOC Removed duplicate 'classes_' attribute in Naive Bayes classifiers (scikit-learn#15811) * BUG Fixes pandas dataframe bug with boolean dtypes (scikit-learn#15797) * BUG Returns only public estimators in all_estimators (scikit-learn#15380) * DOC improve doc for multiclass and types_of_target (scikit-learn#15333) * TST Increases tol for check_pca_float_dtype_preservation assertion (scikit-learn#15775) * update _alpha_grid class in _coordinate_descent.py (scikit-learn#15835) * FIX Explicit conversion of ndarray to object dtype. (scikit-learn#15832) * BLD Parallelize sphinx builds on circle ci (scikit-learn#15745) * DOC correct url for preprocessing (scikit-learn#15853) * MNT avoid generating too many cross links in examples (scikit-learn#15844) * DOC Correct wrong doc in precision_recall_fscore_support (scikit-learn#15833) * DOC add comment in check_pca_float_dtype_preservation (scikit-learn#15819) Documenting the changes in scikit-learn#15775 * DOC correct indents in docstring _split.py (scikit-learn#15843) * DOC fix docstring of KMeans based on sklearn guideline (scikit-learn#15754) * DOC fix docstring of AgglomerativeClustering based on sklearn guideline (scikit-learn#15764) * DOC fix docstring of AffinityPropagation based on sklearn guideline (scikit-learn#15777) * DOC fixed SpectralCoclustering and SpectralBiclustering docstrings following sklearn guideline (scikit-learn#15778) * DOC fix FeatureAgglomeration and MiniBatchKMeans docstring following sklearn guideline (scikit-learn#15809) * TST Specify random_state in test_cv_iterable_wrapper (scikit-learn#15829) * DOC Include LinearSV{C, R} in models that support sample_weights (scikit-learn#15871) * DOC correct some indents (scikit-learn#15875) * DOC Fix documentation of default values in tree classes (scikit-learn#15870) * DOC fix typo in docstring (scikit-learn#15887) * DOC FIX default value for xticks_rotation in plot_confusion_matrix (scikit-learn#15890) * Fix imports in pip3 ubuntu by suffixing affected files (scikit-learn#15891) * MNT Raise erorr when normalize is invalid in confusion_matrix (scikit-learn#15888) * [MRG] DOC Increases search results for API object results (scikit-learn#15574) * MNT Ignores warning in pyamg for deprecated scipy.random (scikit-learn#15914) * DOC Instructions to troubleshoot Windows path length limit (scikit-learn#15916) * DOC add versionadded directive to some estimators (scikit-learn#15849) * DOC clarify doc-string of roc_auc_score and add references (scikit-learn#15293) * MNT Adds skip lint to azure pipeline CI (scikit-learn#15904) * BLD Fixes bug when building with NO_MATHJAX=1 (scikit-learn#15892) * [MRG] BUG Checks to number of axes in passed in ax more generically (scikit-learn#15760) * EXA Minor fixes in plot_sparse_logistic_regression_20newsgroups.py (scikit-learn#15925) * BUG Do not shadow public functions with deprecated modules (scikit-learn#15846) * Import sklearn._distributor_init first (scikit-learn#15929) * DOC Fix typos, via a Levenshtein-style corrector (scikit-learn#15923) * DOC in canned comment, mention that PR title becomes commit me… (scikit-learn#15935) * DOC/EXA Correct spelling of "Classification" (scikit-learn#15938) * BUG fix pip3 ubuntu update by suffixing file (scikit-learn#15928) * [MRG] Ways to compute center_shift_total were different in "full" and "elkan" algorithms. (scikit-learn#15930) * TST Fixes integer test for train and test indices (scikit-learn#15941) * BUG ensure that parallel/sequential give the same permutation importances (scikit-learn#15933) * Formatting fixes in changelog (scikit-learn#15944) * MRG FIX: order of values of self.quantiles_ in QuantileTransformer (scikit-learn#15751) * [MRG] BUG Fixes constrast in plot_confusion_matrix (scikit-learn#15936) * BUG use zero_division argument in classification_report (scikit-learn#15879) * DOC change logreg solver in plot_logistic_path (scikit-learn#15927) * DOC fix whats new ordering (scikit-learn#15961) * COSMIT use np.iinfo to define the max int32 (scikit-learn#15960) * DOC Apply numpydoc validation to VotingRegressor methods (scikit-learn#15969) Co-authored-by: Tiffany R. Williams <Tiffany8@users.noreply.github.com> * DOC improve naive_bayes.py documentation (scikit-learn#15943) Co-authored-by: Jigna Panchal <40188288+jigna-panchal@users.noreply.github.com> * DOC Fix default values in Perceptron documentation (scikit-learn#15965) * DOC Improve default values in logistic documentation (scikit-learn#15966) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * DOC Improve documentation of default values for imputers (scikit-learn#15964) * EXA/MAINT Simplify code in manifold learning example (scikit-learn#15949) * DOC Improve default values in SGD documentation (scikit-learn#15967) * DOC Improve defaults in neural network documentation (scikit-learn#15968) * FIX use safe_sparse_dot for callable kernel in LabelSpreading (scikit-learn#15868) * BUG Adds attributes back to check_is_fitted (scikit-learn#15947) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * DOC update check_is_fitted what's new * DOC change python-devel to python3-devel for yum. (scikit-learn#15986) * DOC Correct the default value of values_format in plot_confusion_matrix (scikit-learn#15981) * [MRG] MNT Updates pypy to use 7.2.0 (scikit-learn#15954) * FIX Add missing 'values_format' param to disp.plot() in plot_confusion_matrix (scikit-learn#15937) * FIX support scalar values in fit_params in SearchCV (scikit-learn#15863) * support a scalar fit param * pep8 * TST add test for desired behavior * FIX introduce _check_fit_params to validate parameters * DOC update whats new * TST tests both grid-search and randomize-search * PEP8 * DOC revert unecessary change * TST add test for _check_fit_params * olivier comments * TST fixes * DOC whats new * DOC whats new * TST revert type of error * add olivier suggestions * address olivier comments * address thomas comments * PEP8 * comments olivier * TST fix test by passing X * avoid to call twice tocsr * add case column/row sparse in check_fit_param * provide optional indices * TST check content when indexing params * PEP8 * TST update tests to check identity * stupid fix * use a distribution in RandomizedSearchCV * MNT add lightgbm to one of the CI build * move to another build * do not install dependencies lightgbm * MNT comments on the CI setup * address some comments * Test fit_params compat without dependency on lightgbm Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * Remove abstractmethod that silently brake downstream packages (scikit-learn#15996) * FIX restore BaseNB._check_X without abstractmethod decoration (scikit-learn#15997) * Update v0.22 changelog for 0.22.1 (scikit-learn#16002) - set the date - move entry for quantile transformer to the 0.22.1 section - fix alphabetical ordering of modules * STY Removes hidden scroll bar (scikit-learn#15999) * Flake8 fixes * Fix: remove left-over lines that should have been deleted during conflict resolution when rebasing * Fix missing imports * Update version * Fix test_check_is_fitted * Make test_sag_regressor_computed_correctly deterministic (scikit-learn#16003) Fix scikit-learn#15818. Co-authored-by: cgsavard <claire.savard@colorado.edu> Co-authored-by: Joel Nothman <joel.nothman@gmail.com> Co-authored-by: Thomas J Fan <thomasjpfan@gmail.com> Co-authored-by: Matt Hall <matt@agilegeoscience.com> Co-authored-by: Kathryn Poole <kathryn.poole2@gmail.com> Co-authored-by: lucyleeow <jliu176@gmail.com> Co-authored-by: JJmistry <jayminm22@gmail.com> Co-authored-by: Juan Carlos Alfaro Jiménez <JuanCarlos.Alfaro@uclm.es> Co-authored-by: SylvainLan <sylvain.s.lannuzel@gmail.com> Co-authored-by: Nicolas Hug <contact@nicolas-hug.com> Co-authored-by: Hanmin Qin <qinhanmin2005@sina.com> Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> Co-authored-by: Vachan D A <vachanda@users.noreply.github.com> Co-authored-by: Sambhav Kothari <sambhavs.email@gmail.com> Co-authored-by: wenliwyan <12013376+wenliwyan@users.noreply.github.com> Co-authored-by: shivamgargsya <shivam.gargshya@gmail.com> Co-authored-by: Reshama Shaikh <rs2715@stern.nyu.edu> Co-authored-by: Oliver Urs Lenz <oulenz@users.noreply.github.com> Co-authored-by: Loïc Estève <loic.esteve@ymail.com> Co-authored-by: Brian Wignall <BrianWignall@gmail.com> Co-authored-by: Ritchie Ng <ritchieng@u.nus.edu> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: inderjeet <43402782+inder128@users.noreply.github.com> Co-authored-by: scibol <scibol@users.noreply.github.com> Co-authored-by: Tirth Patel <tirthasheshpatel@gmail.com> Co-authored-by: Bibhash Chandra Mitra <bibhashm220896@gmail.com> Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org> Co-authored-by: Tiffany R. Williams <Tiffany8@users.noreply.github.com> Co-authored-by: Jigna Panchal <40188288+jigna-panchal@users.noreply.github.com> Co-authored-by: @nkish <19225359+ankishb@users.noreply.github.com> Co-authored-by: Pulkit Mehta <pulkit_mehta_work@yahoo.com> Co-authored-by: David Breuer <DavidBreuer@users.noreply.github.com> Co-authored-by: Niklas <niklas.sm+github@gmail.com> Co-authored-by: Windber <guolipengyeah@126.com> Co-authored-by: Stephen Blystone <29995339+blynotes@users.noreply.github.com> Co-authored-by: Brigitta Sipőcz <b.sipocz@gmail.com>
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Reference Issues/PRs
See #15761.
What does this implement/fix? Explain your changes.
This PR changes the optional parameters to default in
treeclasses, that is,tree.DecisionTreeClassifier,tree.DecisionTreeRegressor,tree.ExtraTreeClassifierandtree.ExtraTreeRegressor.Also, fixes minor issues in error raising to ensure that all of them follow the same format.