tf.contrib.metrics.streaming_sparse_precision_at_k()

tf.contrib.metrics.streaming_sparse_precision_at_k(*args, **kwargs) Computes precision@k of the predictions with respect to sparse

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tf.contrib.metrics.accuracy()

tf.contrib.metrics.accuracy(predictions, labels, weights=None) Computes the percentage of times that predictions matches labels

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tf.contrib.metrics.streaming_percentage_less()

tf.contrib.metrics.streaming_percentage_less(*args, **kwargs) Computes the percentage of values less than the given threshold

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tf.contrib.metrics.streaming_concat()

tf.contrib.metrics.streaming_concat(values, axis=0, max_size=None, metrics_collections=None, updates_collections=None, name=None) Concatenate

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tf.contrib.metrics.streaming_auc()

tf.contrib.metrics.streaming_auc(predictions, labels, weights=None, num_thresholds=200, metrics_collections=None, updates_collections=None, curve='ROC', name=None)

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tf.contrib.metrics.streaming_mean_squared_error()

tf.contrib.metrics.streaming_mean_squared_error(predictions, labels, weights=None, metrics_collections=None, updates_collections=None, name=None)

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tf.contrib.metrics.confusion_matrix()

tf.contrib.metrics.confusion_matrix(predictions, labels, num_classes=None, dtype=tf.int32, name=None, weights=None) Computes the

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tf.contrib.metrics.streaming_mean_absolute_error()

tf.contrib.metrics.streaming_mean_absolute_error(predictions, labels, weights=None, metrics_collections=None, updates_collections=None, name=None)

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tf.contrib.metrics.set_intersection()

tf.contrib.metrics.set_intersection(a, b, validate_indices=True) Compute set intersection of elements in last dimension of a

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tf.contrib.metrics.set_difference()

tf.contrib.metrics.set_difference(a, b, aminusb=True, validate_indices=True) Compute set difference of elements in last dimension

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