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fix: Subclass sklearn.model_selection._RepeatedSplits and BaseShuffleSplit from BaseCrossValidator #349

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Merged
merged 4 commits into from
Feb 13, 2025
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fix: Subclass sklearn.model_selection._RepeatedSplits and BaseShuffleSplit from BaseCrossValidator #349

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b538326
fix: Subclass RepeatedSplits and ShuffleSplits from BaseCrossValidator
effigies Jan 22, 2025
a9acfe3
rf: Drop redundant specification of BaseShuffleSplit
effigies Jan 22, 2025
86b295b
Merge branch 'main' into fix/cv-hierarchy
debonte Jan 30, 2025
5c61724
Merge branch 'main' into fix/cv-hierarchy
effigies Feb 13, 2025
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3 changes: 1 addition & 2 deletions stubs/sklearn/calibration.pyi
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Expand Up @@ -22,7 +22,6 @@ from .base import (
)
from .isotonic import IsotonicRegression
from .model_selection import BaseCrossValidator, check_cv as check_cv, cross_val_predict as cross_val_predict
from .model_selection._split import BaseShuffleSplit
from .preprocessing import LabelEncoder as LabelEncoder, label_binarize as label_binarize
from .svm import LinearSVC as LinearSVC
from .utils import check_matplotlib_support as check_matplotlib_support, column_or_1d as column_or_1d, indexable as indexable
Expand Down Expand Up @@ -51,7 +50,7 @@ class CalibratedClassifierCV(ClassifierMixin, MetaEstimatorMixin, BaseEstimator)
estimator: None | BaseEstimator = None,
*,
method: Literal["sigmoid", "isotonic"] = "sigmoid",
cv: int | BaseCrossValidator | Iterable | None | str | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None | str = None,
n_jobs: None | Int = None,
ensemble: bool = True,
base_estimator: str | BaseEstimator = "deprecated",
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/covariance/_graph_lasso.pyi
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Expand Up @@ -8,7 +8,6 @@ from .._typing import ArrayLike, Float, Int, MatrixLike
from ..exceptions import ConvergenceWarning as ConvergenceWarning
from ..linear_model import lars_path_gram as lars_path_gram
from ..model_selection import BaseCrossValidator, check_cv as check_cv, cross_val_score as cross_val_score
from ..model_selection._split import BaseShuffleSplit
from ..utils._param_validation import Interval as Interval, StrOptions as StrOptions
from ..utils.parallel import Parallel as Parallel, delayed as delayed
from ..utils.validation import check_random_state as check_random_state, check_scalar as check_scalar
Expand Down Expand Up @@ -117,7 +116,7 @@ class GraphicalLassoCV(BaseGraphicalLasso):
*,
alphas: ArrayLike | int = 4,
n_refinements: Int = 4,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
tol: Float = 1e-4,
enet_tol: Float = 1e-4,
max_iter: Int = 100,
Expand Down
5 changes: 2 additions & 3 deletions stubs/sklearn/ensemble/_stacking.pyi
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Expand Up @@ -19,7 +19,6 @@ from ..exceptions import NotFittedError as NotFittedError
from ..linear_model._logistic import LogisticRegression
from ..linear_model._ridge import RidgeCV
from ..model_selection import BaseCrossValidator, check_cv as check_cv, cross_val_predict as cross_val_predict
from ..model_selection._split import BaseShuffleSplit
from ..pipeline import Pipeline
from ..preprocessing import LabelEncoder as LabelEncoder
from ..utils import Bunch
Expand Down Expand Up @@ -78,7 +77,7 @@ class StackingClassifier(ClassifierMixin, _BaseStacking):
estimators: Sequence[tuple[str, BaseEstimator]],
final_estimator: None | BaseEstimator | LogisticRegression = None,
*,
cv: int | BaseCrossValidator | Iterable | None | str | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None | str = None,
stack_method: Literal["auto", "predict_proba", "decision_function", "predict"] = "auto",
n_jobs: None | Int = None,
passthrough: bool = False,
Expand Down Expand Up @@ -108,7 +107,7 @@ class StackingRegressor(RegressorMixin, _BaseStacking):
estimators: Sequence[tuple[str, BaseEstimator]] | list[tuple[str, Pipeline]],
final_estimator: None | BaseEstimator | RidgeCV = None,
*,
cv: int | BaseCrossValidator | Iterable | None | str | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None | str = None,
n_jobs: None | Int = None,
passthrough: bool = False,
verbose: Int = 0,
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/feature_selection/_rfe.pyi
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Expand Up @@ -9,7 +9,6 @@ from ..base import BaseEstimator, MetaEstimatorMixin, clone as clone, is_classif
from ..linear_model._logistic import LogisticRegression
from ..metrics import check_scoring as check_scoring
from ..model_selection import BaseCrossValidator, check_cv as check_cv
from ..model_selection._split import BaseShuffleSplit
from ..utils._param_validation import HasMethods as HasMethods, Interval as Interval
from ..utils.metaestimators import available_if as available_if
from ..utils.parallel import Parallel as Parallel, delayed as delayed
Expand Down Expand Up @@ -73,7 +72,7 @@ class RFECV(RFE):
*,
step: float = 1,
min_features_to_select: Int = 1,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
scoring: None | str | Callable = None,
verbose: Int = 0,
n_jobs: None | int = None,
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/feature_selection/_sequential.pyi
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Expand Up @@ -7,7 +7,6 @@ from .._typing import ArrayLike, Float, Int, MatrixLike
from ..base import BaseEstimator, MetaEstimatorMixin, clone as clone
from ..metrics import get_scorer_names as get_scorer_names
from ..model_selection import BaseCrossValidator, cross_val_score as cross_val_score
from ..model_selection._split import BaseShuffleSplit
from ..utils._param_validation import HasMethods as HasMethods, Hidden as Hidden, Interval as Interval, StrOptions as StrOptions
from ..utils.validation import check_is_fitted as check_is_fitted
from ._base import SelectorMixin
Expand All @@ -34,7 +33,7 @@ class SequentialFeatureSelector(SelectorMixin, MetaEstimatorMixin, BaseEstimator
tol: None | Float = None,
direction: Literal["forward", "backward"] = "forward",
scoring: None | str | Callable = None,
cv: Iterable | int | BaseShuffleSplit | BaseCrossValidator = 5,
cv: Iterable | int | BaseCrossValidator = 5,
n_jobs: None | Int = None,
) -> None: ...
def fit(
Expand Down
9 changes: 4 additions & 5 deletions stubs/sklearn/linear_model/_coordinate_descent.pyi
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Expand Up @@ -13,7 +13,6 @@ from scipy.sparse._coo import coo_matrix
from .._typing import ArrayLike, Float, Int, MatrixLike
from ..base import MultiOutputMixin, RegressorMixin
from ..model_selection import BaseCrossValidator, check_cv as check_cv
from ..model_selection._split import BaseShuffleSplit
from ..utils import check_array as check_array, check_scalar as check_scalar
from ..utils._param_validation import Interval as Interval, StrOptions as StrOptions
from ..utils.extmath import safe_sparse_dot as safe_sparse_dot
Expand Down Expand Up @@ -206,7 +205,7 @@ class LassoCV(RegressorMixin, LinearModelCV):
max_iter: Int = 1000,
tol: Float = 1e-4,
copy_X: bool = True,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
verbose: int | bool = False,
n_jobs: None | Int = None,
positive: bool = False,
Expand Down Expand Up @@ -241,7 +240,7 @@ class ElasticNetCV(RegressorMixin, LinearModelCV):
precompute: Literal["auto"] | MatrixLike | bool = "auto",
max_iter: Int = 1000,
tol: Float = 1e-4,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
copy_X: bool = True,
verbose: int | bool = 0,
n_jobs: None | Int = None,
Expand Down Expand Up @@ -333,7 +332,7 @@ class MultiTaskElasticNetCV(RegressorMixin, LinearModelCV):
fit_intercept: bool = True,
max_iter: Int = 1000,
tol: Float = 1e-4,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
copy_X: bool = True,
verbose: int | bool = 0,
n_jobs: None | Int = None,
Expand Down Expand Up @@ -370,7 +369,7 @@ class MultiTaskLassoCV(RegressorMixin, LinearModelCV):
max_iter: Int = 1000,
tol: Float = 1e-4,
copy_X: bool = True,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
verbose: int | bool = False,
n_jobs: None | Int = None,
random_state: RandomState | None | Int = None,
Expand Down
5 changes: 2 additions & 3 deletions stubs/sklearn/linear_model/_least_angle.pyi
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Expand Up @@ -11,7 +11,6 @@ from .._typing import ArrayLike, Float, Int, MatrixLike
from ..base import MultiOutputMixin, RegressorMixin
from ..exceptions import ConvergenceWarning as ConvergenceWarning
from ..model_selection import BaseCrossValidator, check_cv as check_cv
from ..model_selection._split import BaseShuffleSplit
from ..utils import arrayfuncs as arrayfuncs, as_float_array as as_float_array, check_random_state as check_random_state
from ..utils._param_validation import Hidden as Hidden, Interval as Interval, StrOptions as StrOptions
from ..utils.parallel import Parallel as Parallel, delayed as delayed
Expand Down Expand Up @@ -160,7 +159,7 @@ class LarsCV(Lars):
max_iter: Int = 500,
normalize: str | bool = "deprecated",
precompute: Literal["auto"] | ArrayLike | bool = "auto",
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
max_n_alphas: Int = 1000,
n_jobs: None | int = None,
eps: Float = ...,
Expand Down Expand Up @@ -193,7 +192,7 @@ class LassoLarsCV(LarsCV):
max_iter: Int = 500,
normalize: str | bool = "deprecated",
precompute: Literal["auto"] | bool = "auto",
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
max_n_alphas: Int = 1000,
n_jobs: None | int = None,
eps: Float = ...,
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/linear_model/_logistic.pyi
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Expand Up @@ -10,7 +10,6 @@ from .._loss.loss import HalfBinomialLoss as HalfBinomialLoss, HalfMultinomialLo
from .._typing import ArrayLike, Float, Int, MatrixLike
from ..metrics import get_scorer as get_scorer, get_scorer_names as get_scorer_names
from ..model_selection import BaseCrossValidator, check_cv as check_cv
from ..model_selection._split import BaseShuffleSplit
from ..preprocessing import LabelBinarizer as LabelBinarizer, LabelEncoder as LabelEncoder
from ..utils import (
check_array as check_array,
Expand Down Expand Up @@ -108,7 +107,7 @@ class LogisticRegressionCV(LogisticRegression, LinearClassifierMixin, BaseEstima
*,
Cs: Sequence[float] | int = 10,
fit_intercept: bool = True,
cv: int | None | BaseShuffleSplit | BaseCrossValidator = None,
cv: int | None | BaseCrossValidator = None,
dual: bool = False,
penalty: Literal["l1", "l2", "elasticnet"] = "l2",
scoring: None | str | Callable = None,
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/linear_model/_omp.pyi
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Expand Up @@ -9,7 +9,6 @@ from scipy.linalg.lapack import get_lapack_funcs as get_lapack_funcs
from .._typing import ArrayLike, Float, Int, MatrixLike
from ..base import MultiOutputMixin, RegressorMixin
from ..model_selection import BaseCrossValidator, check_cv as check_cv
from ..model_selection._split import BaseShuffleSplit
from ..utils import as_float_array as as_float_array, check_array as check_array
from ..utils._param_validation import Hidden as Hidden, Interval as Interval, StrOptions as StrOptions
from ..utils.parallel import Parallel as Parallel, delayed as delayed
Expand Down Expand Up @@ -90,7 +89,7 @@ class OrthogonalMatchingPursuitCV(RegressorMixin, LinearModel):
fit_intercept: bool = True,
normalize: str | bool = "deprecated",
max_iter: None | Int = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
n_jobs: None | Int = None,
verbose: int | bool = False,
) -> None: ...
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/linear_model/_ridge.pyi
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Expand Up @@ -18,7 +18,6 @@ from ..base import MultiOutputMixin, RegressorMixin, is_classifier as is_classif
from ..exceptions import ConvergenceWarning as ConvergenceWarning
from ..metrics import check_scoring as check_scoring, get_scorer_names as get_scorer_names
from ..model_selection import BaseCrossValidator, GridSearchCV as GridSearchCV
from ..model_selection._split import BaseShuffleSplit
from ..preprocessing import LabelBinarizer as LabelBinarizer
from ..utils import (
check_array as check_array,
Expand Down Expand Up @@ -237,7 +236,7 @@ class RidgeClassifierCV(_RidgeClassifierMixin, _BaseRidgeCV):
*,
fit_intercept: bool = True,
scoring: None | str | Callable = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
class_weight: None | Mapping | str = None,
store_cv_values: bool = False,
) -> None: ...
Expand Down
3 changes: 1 addition & 2 deletions stubs/sklearn/model_selection/_plot.pyi
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Expand Up @@ -9,7 +9,6 @@ from numpy.random import RandomState
from .._typing import ArrayLike, Float, Int, MatrixLike
from ..utils import check_matplotlib_support as check_matplotlib_support
from . import BaseCrossValidator, learning_curve as learning_curve
from ._split import BaseShuffleSplit

class LearningCurveDisplay:
fill_between_: Artist | None = ...
Expand Down Expand Up @@ -48,7 +47,7 @@ class LearningCurveDisplay:
*,
groups: None | ArrayLike = None,
train_sizes: ArrayLike = ...,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
scoring: None | str | Callable = None,
exploit_incremental_learning: bool = False,
n_jobs: None | Int = None,
Expand Down
6 changes: 3 additions & 3 deletions stubs/sklearn/model_selection/_search.pyi
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Expand Up @@ -21,7 +21,7 @@ from ..utils.parallel import Parallel as Parallel, delayed as delayed
from ..utils.random import sample_without_replacement as sample_without_replacement
from ..utils.validation import check_is_fitted as check_is_fitted, indexable as indexable
from . import BaseCrossValidator
from ._split import BaseShuffleSplit, check_cv as check_cv
from ._split import check_cv as check_cv

BaseSearchCV_Self = TypeVar("BaseSearchCV_Self", bound=BaseSearchCV)
BaseEstimatorT = TypeVar("BaseEstimatorT", bound=BaseEstimator, default=BaseEstimator, covariant=True)
Expand Down Expand Up @@ -110,7 +110,7 @@ class GridSearchCV(BaseSearchCV, Generic[BaseEstimatorT]):
scoring: ArrayLike | None | tuple | Callable | Mapping | str = None,
n_jobs: None | Int = None,
refit: str | Callable | bool = True,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
verbose: Int = 0,
pre_dispatch: str | int = "2*n_jobs",
error_score: str | Float = ...,
Expand Down Expand Up @@ -142,7 +142,7 @@ class RandomizedSearchCV(BaseSearchCV):
scoring: ArrayLike | None | tuple | Callable | Mapping | str = None,
n_jobs: None | Int = None,
refit: str | Callable | bool = True,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
verbose: Int = 0,
pre_dispatch: str | int = "2*n_jobs",
random_state: RandomState | None | Int = None,
Expand Down
6 changes: 3 additions & 3 deletions stubs/sklearn/model_selection/_search_successive_halving.pyi
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Expand Up @@ -14,7 +14,7 @@ from ..utils import resample as resample
from ..utils.multiclass import check_classification_targets as check_classification_targets
from . import BaseCrossValidator, ParameterGrid as ParameterGrid, ParameterSampler as ParameterSampler
from ._search import BaseSearchCV
from ._split import BaseShuffleSplit, check_cv as check_cv
from ._split import check_cv as check_cv

BaseSuccessiveHalving_Self = TypeVar("BaseSuccessiveHalving_Self", bound=BaseSuccessiveHalving)

Expand Down Expand Up @@ -87,7 +87,7 @@ class HalvingGridSearchCV(BaseSuccessiveHalving):
max_resources: str | Int = "auto",
min_resources: int | Literal["exhaust", "smallest"] = "exhaust",
aggressive_elimination: bool = False,
cv: Iterable | int | BaseShuffleSplit | BaseCrossValidator = 5,
cv: Iterable | int | BaseCrossValidator = 5,
scoring: None | str | Callable = None,
refit: bool = True,
error_score: str | Float = ...,
Expand Down Expand Up @@ -132,7 +132,7 @@ class HalvingRandomSearchCV(BaseSuccessiveHalving):
max_resources: str | Int = "auto",
min_resources: Literal["exhaust", "smallest"] | int = "smallest",
aggressive_elimination: bool = False,
cv: Iterable | int | BaseShuffleSplit | BaseCrossValidator = 5,
cv: Iterable | int | BaseCrossValidator = 5,
scoring: None | str | Callable = None,
refit: bool = True,
error_score: str | Float = ...,
Expand Down
8 changes: 4 additions & 4 deletions stubs/sklearn/model_selection/_split.pyi
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Expand Up @@ -46,7 +46,7 @@ class BaseCrossValidator(metaclass=ABCMeta):
groups: None | ArrayLike = None,
) -> Iterator[tuple[ndarray, ndarray]]: ...
@abstractmethod
def get_n_splits(self, X=None, y=None, groups=None): ...
def get_n_splits(self, X=None, y=None, groups=None) -> int: ...

class LeaveOneOut(BaseCrossValidator):
def get_n_splits(self, X: MatrixLike, y: Any = None, groups: Any = None) -> int: ...
Expand Down Expand Up @@ -119,7 +119,7 @@ class LeavePGroupsOut(BaseCrossValidator):
def get_n_splits(self, X: Any = None, y: Any = None, groups: None | ArrayLike = None) -> int: ...
def split(self, X: MatrixLike, y: None | ArrayLike = None, groups: None | ArrayLike = None): ...

class _RepeatedSplits(metaclass=ABCMeta):
class _RepeatedSplits(BaseCrossValidator, metaclass=ABCMeta):
def __init__(
self,
cv: Callable,
Expand Down Expand Up @@ -151,7 +151,7 @@ class RepeatedStratifiedKFold(_RepeatedSplits):
random_state: RandomState | None | Int = None,
) -> None: ...

class BaseShuffleSplit(metaclass=ABCMeta):
class BaseShuffleSplit(BaseCrossValidator, metaclass=ABCMeta):
def __init__(self, n_splits: int = 10, *, test_size=None, train_size=None, random_state=None) -> None: ...
def split(
self, X: MatrixLike, y: None | ArrayLike = None, groups: None | ArrayLike = None
Expand Down Expand Up @@ -201,7 +201,7 @@ class _CVIterableWrapper(BaseCrossValidator):
def split(self, X: Any = None, y: Any = None, groups: Any = None): ...

def check_cv(
cv: Iterable | int | BaseShuffleSplit | BaseCrossValidator | None = 5,
cv: Iterable | int | BaseCrossValidator | None = 5,
y: None | ArrayLike = None,
*,
classifier: bool = False,
Expand Down
14 changes: 7 additions & 7 deletions stubs/sklearn/model_selection/_validation.pyi
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Expand Up @@ -22,7 +22,7 @@ from ..svm._classes import SVC, LinearSVC
from ..utils import check_random_state as check_random_state, indexable as indexable
from ..utils.parallel import Parallel as Parallel, delayed as delayed
from . import BaseCrossValidator
from ._split import BaseShuffleSplit, check_cv as check_cv
from ._split import check_cv as check_cv

# Author: Alexandre Gramfort <[email protected]>
# Gael Varoquaux <[email protected]>
Expand All @@ -47,7 +47,7 @@ def cross_validate(
*,
groups: None | ArrayLike = None,
scoring: ArrayLike | None | tuple | Callable | Mapping | str = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
n_jobs: None | Int = None,
verbose: Int = 0,
fit_params: None | dict = None,
Expand All @@ -63,7 +63,7 @@ def cross_val_score(
*,
groups: None | ArrayLike = None,
scoring: None | str | Callable = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
n_jobs: None | Int = None,
verbose: Int = 0,
fit_params: None | dict = None,
Expand All @@ -76,7 +76,7 @@ def cross_val_predict(
y: None | MatrixLike | ArrayLike = None,
*,
groups: None | ArrayLike = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
n_jobs: None | Int = None,
verbose: Int = 0,
fit_params: None | dict = None,
Expand All @@ -89,7 +89,7 @@ def permutation_test_score(
y: None | MatrixLike | ArrayLike,
*,
groups: None | ArrayLike = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
n_permutations: Int = 100,
n_jobs: None | Int = None,
random_state: RandomState | None | Int = 0,
Expand All @@ -104,7 +104,7 @@ def learning_curve(
*,
groups: None | ArrayLike = None,
train_sizes: ArrayLike = ...,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
scoring: None | str | Callable = None,
exploit_incremental_learning: bool = False,
n_jobs: None | Int = None,
Expand All @@ -124,7 +124,7 @@ def validation_curve(
param_name: str,
param_range: ArrayLike,
groups: None | ArrayLike = None,
cv: int | BaseCrossValidator | Iterable | None | BaseShuffleSplit = None,
cv: int | BaseCrossValidator | Iterable | None = None,
scoring: None | str | Callable = None,
n_jobs: None | Int = None,
pre_dispatch: str | Int = "all",
Expand Down
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