90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
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import typing
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from ._split import BaseCrossValidator
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from ._split import BaseShuffleSplit
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from ._split import KFold
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from ._split import GroupKFold
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from ._split import StratifiedKFold
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from ._split import TimeSeriesSplit
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from ._split import LeaveOneGroupOut
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from ._split import LeaveOneOut
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from ._split import LeavePGroupsOut
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from ._split import LeavePOut
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from ._split import RepeatedKFold
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from ._split import RepeatedStratifiedKFold
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from ._split import ShuffleSplit
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from ._split import GroupShuffleSplit
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from ._split import StratifiedShuffleSplit
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from ._split import StratifiedGroupKFold
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from ._split import PredefinedSplit
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from ._split import train_test_split
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from ._split import check_cv
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from ._validation import cross_val_score
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from ._validation import cross_val_predict
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from ._validation import cross_validate
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from ._validation import learning_curve
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from ._validation import permutation_test_score
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from ._validation import validation_curve
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from ._search import GridSearchCV
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from ._search import RandomizedSearchCV
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from ._search import ParameterGrid
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from ._search import ParameterSampler
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from ._plot import LearningCurveDisplay
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if typing.TYPE_CHECKING:
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# Avoid errors in type checkers (e.g. mypy) for experimental estimators.
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# TODO: remove this check once the estimator is no longer experimental.
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from ._search_successive_halving import ( # noqa
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HalvingGridSearchCV,
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HalvingRandomSearchCV,
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)
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__all__ = [
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"BaseCrossValidator",
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"BaseShuffleSplit",
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"GridSearchCV",
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"TimeSeriesSplit",
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"KFold",
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"GroupKFold",
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"GroupShuffleSplit",
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"LeaveOneGroupOut",
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"LeaveOneOut",
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"LeavePGroupsOut",
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"LeavePOut",
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"RepeatedKFold",
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"RepeatedStratifiedKFold",
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"ParameterGrid",
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"ParameterSampler",
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"PredefinedSplit",
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"RandomizedSearchCV",
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"ShuffleSplit",
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"StratifiedKFold",
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"StratifiedGroupKFold",
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"StratifiedShuffleSplit",
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"check_cv",
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"cross_val_predict",
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"cross_val_score",
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"cross_validate",
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"learning_curve",
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"LearningCurveDisplay",
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"permutation_test_score",
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"train_test_split",
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"validation_curve",
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]
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# TODO: remove this check once the estimator is no longer experimental.
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def __getattr__(name):
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if name in {"HalvingGridSearchCV", "HalvingRandomSearchCV"}:
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raise ImportError(
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f"{name} is experimental and the API might change without any "
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"deprecation cycle. To use it, you need to explicitly import "
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"enable_halving_search_cv:\n"
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"from sklearn.experimental import enable_halving_search_cv"
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)
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raise AttributeError(f"module {__name__} has no attribute {name}")
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