matchzoo.metrics.cross_entropy
¶
CrossEntropy metric for Classification.
Module Contents¶
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class
matchzoo.metrics.cross_entropy.
CrossEntropy
¶ Bases:
matchzoo.engine.base_metric.ClassificationMetric
Cross entropy metric.
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ALIAS
= ['cross_entropy', 'ce']¶
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__repr__
(self)¶ Returns: Formated string representation of the metric.
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__call__
(self, y_true: np.array, y_pred: np.array, eps: float = 1e-12)¶ Calculate cross entropy.
Example
>>> y_true = [0, 1] >>> y_pred = [[0.25, 0.25], [0.01, 0.90]] >>> CrossEntropy()(y_true, y_pred) 0.7458274358333028
Parameters: - y_true – The ground true label of each document.
- y_pred – The predicted scores of each document.
- eps – The Log loss is undefined for p=0 or p=1, so probabilities are clipped to max(eps, min(1 - eps, p)).
Returns: Average precision.
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