sklearn.base
.ClassifierMixin¶
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class
sklearn.base.
ClassifierMixin
[source]¶ Mixin class for all classifiers in scikit-learn.
Methods
score
(X, y[, sample_weight])Return 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.
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score
(X, y, sample_weight=None)[source]¶ Return 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 of shape (n_samples, n_features)
Test samples.
y : array-like of shape (n_samples,) or (n_samples, n_outputs)
True labels for X.
sample_weight : array-like of shape (n_samples,), default=None
Sample weights.
- Returns
score : float
Mean accuracy of self.predict(X) wrt. y.
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