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- """Transformers for missing value imputation"""
- import typing
- from ._base import MissingIndicator, SimpleImputer
- from ._knn import KNNImputer
- if typing.TYPE_CHECKING:
- # Avoid errors in type checkers (e.g. mypy) for experimental estimators.
- # TODO: remove this check once the estimator is no longer experimental.
- from ._iterative import IterativeImputer # noqa
- __all__ = ["MissingIndicator", "SimpleImputer", "KNNImputer"]
- # TODO: remove this check once the estimator is no longer experimental.
- def __getattr__(name):
- if name == "IterativeImputer":
- raise ImportError(
- f"{name} is experimental and the API might change without any "
- "deprecation cycle. To use it, you need to explicitly import "
- "enable_iterative_imputer:\n"
- "from sklearn.experimental import enable_iterative_imputer"
- )
- raise AttributeError(f"module {__name__} has no attribute {name}")
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