40 lines
1.6 KiB
Python
40 lines
1.6 KiB
Python
"""
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The :mod:`sklearn.ensemble` module includes ensemble-based methods for
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classification, regression and anomaly detection.
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"""
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import typing
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from ._base import BaseEnsemble
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from ._forest import RandomForestClassifier
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from ._forest import RandomForestRegressor
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from ._forest import RandomTreesEmbedding
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from ._forest import ExtraTreesClassifier
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from ._forest import ExtraTreesRegressor
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from ._bagging import BaggingClassifier
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from ._bagging import BaggingRegressor
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from ._iforest import IsolationForest
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from ._weight_boosting import AdaBoostClassifier
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from ._weight_boosting import AdaBoostRegressor
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from ._gb import GradientBoostingClassifier
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from ._gb import GradientBoostingRegressor
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from ._voting import VotingClassifier
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from ._voting import VotingRegressor
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from ._stacking import StackingClassifier
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from ._stacking import StackingRegressor
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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 ._hist_gradient_boosting.gradient_boosting import ( # noqa
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HistGradientBoostingRegressor, HistGradientBoostingClassifier
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)
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__all__ = ["BaseEnsemble",
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"RandomForestClassifier", "RandomForestRegressor",
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"RandomTreesEmbedding", "ExtraTreesClassifier",
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"ExtraTreesRegressor", "BaggingClassifier",
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"BaggingRegressor", "IsolationForest", "GradientBoostingClassifier",
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"GradientBoostingRegressor", "AdaBoostClassifier",
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"AdaBoostRegressor", "VotingClassifier", "VotingRegressor",
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"StackingClassifier", "StackingRegressor",
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]
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