forked from scikit-learn/scikit-learn
-
Notifications
You must be signed in to change notification settings - Fork 0
/
__init__.py
74 lines (68 loc) · 2.02 KB
/
__init__.py
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
import typing
from ._split import BaseCrossValidator
from ._split import BaseShuffleSplit
from ._split import KFold
from ._split import GroupKFold
from ._split import StratifiedKFold
from ._split import TimeSeriesSplit
from ._split import LeaveOneGroupOut
from ._split import LeaveOneOut
from ._split import LeavePGroupsOut
from ._split import LeavePOut
from ._split import RepeatedKFold
from ._split import RepeatedStratifiedKFold
from ._split import ShuffleSplit
from ._split import GroupShuffleSplit
from ._split import StratifiedShuffleSplit
from ._split import StratifiedGroupKFold
from ._split import PredefinedSplit
from ._split import train_test_split
from ._split import check_cv
from ._validation import cross_val_score
from ._validation import cross_val_predict
from ._validation import cross_validate
from ._validation import learning_curve
from ._validation import permutation_test_score
from ._validation import validation_curve
from ._search import GridSearchCV
from ._search import RandomizedSearchCV
from ._search import ParameterGrid
from ._search import ParameterSampler
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
HalvingGridSearchCV,
HalvingRandomSearchCV,
)
__all__ = [
"BaseCrossValidator",
"BaseShuffleSplit",
"GridSearchCV",
"TimeSeriesSplit",
"KFold",
"GroupKFold",
"GroupShuffleSplit",
"LeaveOneGroupOut",
"LeaveOneOut",
"LeavePGroupsOut",
"LeavePOut",
"RepeatedKFold",
"RepeatedStratifiedKFold",
"ParameterGrid",
"ParameterSampler",
"PredefinedSplit",
"RandomizedSearchCV",
"ShuffleSplit",
"StratifiedKFold",
"StratifiedGroupKFold",
"StratifiedShuffleSplit",
"check_cv",
"cross_val_predict",
"cross_val_score",
"cross_validate",
"learning_curve",
"permutation_test_score",
"train_test_split",
"validation_curve",
]