Warning
DEPRECATED
-
sklearn.cross_validation.check_cv(cv, X=None, y=None, classifier=False)
[source] -
Input checker utility for building a CV in a user friendly way.
Deprecated since version 0.18: This module will be removed in 0.20. Use
sklearn.model_selection.check_cv
instead.Parameters: cv : int, cross-validation generator or an iterable, optional
Determines the cross-validation splitting strategy. Possible inputs for cv are:
- None, to use the default 3-fold cross-validation,
- integer, to specify the number of folds.
- An object to be used as a cross-validation generator.
- An iterable yielding train/test splits.
For integer/None inputs, if classifier is True and
y
is binary or multiclass,StratifiedKFold
is used. In all other cases,KFold
is used.Refer User Guide for the various cross-validation strategies that can be used here.
X : array-like
The data the cross-val object will be applied on.
y : array-like
The target variable for a supervised learning problem.
classifier : boolean optional
Whether the task is a classification task, in which case stratified KFold will be used.
Returns: checked_cv: a cross-validation generator instance. :
The return value is guaranteed to be a cv generator instance, whatever the input type.
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