1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
|
"""Tools for model selection, such as cross validation and hyper-parameter tuning."""
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
import typing
from ._classification_threshold import (
FixedThresholdClassifier,
TunedThresholdClassifierCV,
)
from ._plot import LearningCurveDisplay, ValidationCurveDisplay
from ._search import GridSearchCV, ParameterGrid, ParameterSampler, RandomizedSearchCV
from ._split import (
BaseCrossValidator,
BaseShuffleSplit,
GroupKFold,
GroupShuffleSplit,
KFold,
LeaveOneGroupOut,
LeaveOneOut,
LeavePGroupsOut,
LeavePOut,
PredefinedSplit,
RepeatedKFold,
RepeatedStratifiedKFold,
ShuffleSplit,
StratifiedGroupKFold,
StratifiedKFold,
StratifiedShuffleSplit,
TimeSeriesSplit,
check_cv,
train_test_split,
)
from ._validation import (
cross_val_predict,
cross_val_score,
cross_validate,
learning_curve,
permutation_test_score,
validation_curve,
)
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 ._search_successive_halving import ( # noqa: F401
HalvingGridSearchCV,
HalvingRandomSearchCV,
)
__all__ = [
"BaseCrossValidator",
"BaseShuffleSplit",
"FixedThresholdClassifier",
"GridSearchCV",
"GroupKFold",
"GroupShuffleSplit",
"KFold",
"LearningCurveDisplay",
"LeaveOneGroupOut",
"LeaveOneOut",
"LeavePGroupsOut",
"LeavePOut",
"ParameterGrid",
"ParameterSampler",
"PredefinedSplit",
"RandomizedSearchCV",
"RepeatedKFold",
"RepeatedStratifiedKFold",
"ShuffleSplit",
"StratifiedGroupKFold",
"StratifiedKFold",
"StratifiedShuffleSplit",
"TimeSeriesSplit",
"TunedThresholdClassifierCV",
"ValidationCurveDisplay",
"check_cv",
"cross_val_predict",
"cross_val_score",
"cross_validate",
"learning_curve",
"permutation_test_score",
"train_test_split",
"validation_curve",
]
# TODO: remove this check once the estimator is no longer experimental.
def __getattr__(name):
if name in {"HalvingGridSearchCV", "HalvingRandomSearchCV"}:
raise ImportError(
f"{name} is experimental and the API might change without any "
"deprecation cycle. To use it, you need to explicitly import "
"enable_halving_search_cv:\n"
"from sklearn.experimental import enable_halving_search_cv"
)
raise AttributeError(f"module {__name__} has no attribute {name}")
|
