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"""Transformers for missing value imputation."""
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
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: F401
__all__ = ["KNNImputer", "MissingIndicator", "SimpleImputer"]
# 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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