# sklearn.base.ClassifierMixin¶

class sklearn.base.ClassifierMixin[source]

Mixin class for all classifiers in scikit-learn.

Methods

 score(self, 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(self, 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. score : float Mean accuracy of self.predict(X) wrt. y.