Class ConfidenceMetricsEntry (2.7.3) 

ConfidenceMetricsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Metrics for a single confidence threshold.

Attributes

NameDescription
confidence_threshold float
Output only. Metrics are computed with an assumption that the model never returns predictions with score lower than this value.
position_threshold int
Output only. Metrics are computed with an assumption that the model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the confidence_threshold.
recall float
Output only. Recall (True Positive Rate) for the given confidence threshold.
precision float
Output only. Precision for the given confidence threshold.
false_positive_rate float
Output only. False Positive Rate for the given confidence threshold.
f1_score float
Output only. The harmonic mean of recall and precision.
recall_at1 float
Output only. The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each example.
precision_at1 float
Output only. The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each example.
false_positive_rate_at1 float
Output only. The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each example.
f1_score_at1 float
Output only. The harmonic mean of recall_at1 and precision_at1.
true_positive_count int
Output only. The number of model created labels that match a ground truth label.
false_positive_count int
Output only. The number of model created labels that do not match a ground truth label.
false_negative_count int
Output only. The number of ground truth labels that are not matched by a model created label.
true_negative_count int
Output only. The number of labels that were not created by the model, but if they would, they would not match a ground truth label.