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class sklearn.base.ClassifierMixin
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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__()
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x.__init__(...) initializes x; see help(type(x)) for signature
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score(X, y, sample_weight=None)
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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.
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base.ClassifierMixin
2017-01-15 04:20:32
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