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__()

x.__init__(...) initializes x; see help(type(x)) for 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.