tf.contrib.metrics.streaming_recall_at_k(*args, **kwargs) Computes the recall@k of the predictions with respect to dense labels

tf.contrib.metrics.streaming_specificity_at_sensitivity(predictions, labels, sensitivity, weights=None, num_thresholds=200, metrics_collections=None, updates_collections=None

tf.contrib.metrics.aggregate_metric_map(names_to_tuples) Aggregates the metric names to tuple dictionary. This

tf.contrib.metrics.auc_using_histogram(boolean_labels, scores, score_range, nbins=100, collections=None, check_shape=True, name=None) AUC

tf.contrib.metrics.streaming_sensitivity_at_specificity(predictions, labels, specificity, weights=None, num_thresholds=200, metrics_collections=None, updates_collections=None

Contents Metrics (contrib)Ops for evaluation metrics and summary statistics.API Metric Ops tf

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

tf.contrib.metrics.streaming_precision(*args, **kwargs) Computes the precision of the predictions with respect to the labels.

tf.contrib.metrics.aggregate_metrics(*value_update_tuples) Aggregates the metric value tensors and update ops into two lists.

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