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GridSearchCV (or rather check_cv) doesn't handle 2d y #9742

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amueller opened this issue Sep 12, 2017 · 1 comment
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GridSearchCV (or rather check_cv) doesn't handle 2d y #9742

amueller opened this issue Sep 12, 2017 · 1 comment

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@amueller
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Via #9741.

from sklearn.model_selection import GridSearchCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_blobs
X, y = make_blobs()

grid = GridSearchCV(LogisticRegression(), {'C': [.1, 1]})
grid.fit(X, y.reshape(-1, 1))

IndexError: too many indices for array

While

from sklearn.model_selection import KFold
grid = GridSearchCV(LogisticRegression(), {'C': [.1, 1]}, cv=KFold(3))
grid.fit(X, y.reshape(-1, 1))

works and raises DataConversionWarning.
I'm pretty sure using multi-label y will also crash.
@amueller
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ah, multi-label y will actually default to KFold, but because

from sklearn.utils.multiclass import type_of_target
type_of_target(y.reshape(-1, 1))

'multiclass'

we're using StratifiedKFold here but don't convert y.

@amueller amueller mentioned this issue Sep 12, 2017
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@amueller