sklearn.base.ClassifierMixin — scikit-learn 0.20.4 documentation (original) (raw)
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. |
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__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. |
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| Returns: | score : float Mean accuracy of self.predict(X) wrt. y. |