sklearn.base
.ClassifierMixin¶
-
class
sklearn.base.
ClassifierMixin
[source]¶ Mixin class for all classifiers in scikit-learn.
Methods
score
(X, y[, sample_weight])Returns the mean accuracy on the given test data and labels. -
__init__
($self, /, *args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
-
score
(X, y, sample_weight=None)[source]¶ Returns the mean accuracy on the given test data and labels.
In multi-label classification, this is the subset accuracy which is a harsh metric since you require for each sample that each label set be correctly predicted.
Parameters: - X : array-like, shape = (n_samples, n_features)
Test samples.
- y : array-like, shape = (n_samples) or (n_samples, n_outputs)
True labels for X.
- sample_weight : array-like, shape = [n_samples], optional
Sample weights.
Returns: - score : float
Mean accuracy of self.predict(X) wrt. y.
-