Class MultiConfidenceMetrics (2.21.1) 

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

Metrics across multiple confidence levels.

Attributes

NameDescription
confidence_level_metrics MutableSequence[google.cloud.documentai_v1.types.Evaluation.ConfidenceLevelMetrics]
Metrics across confidence levels with fuzzy matching enabled.
confidence_level_metrics_exact MutableSequence[google.cloud.documentai_v1.types.Evaluation.ConfidenceLevelMetrics]
Metrics across confidence levels with only exact matching.
auprc float
The calculated area under the precision recall curve (AUPRC), computed by integrating over all confidence thresholds.
estimated_calibration_error float
The Estimated Calibration Error (ECE) of the confidence of the predicted entities.
auprc_exact float
The AUPRC for metrics with fuzzy matching disabled, i.e., exact matching only.
estimated_calibration_error_exact float
The ECE for the predicted entities with fuzzy matching disabled, i.e., exact matching only.
metrics_type google.cloud.documentai_v1.types.Evaluation.MultiConfidenceMetrics.MetricsType
The metrics type for the label.

Classes

MetricsType

MetricsType(value)

A type that determines how metrics should be interpreted.

Values: METRICS_TYPE_UNSPECIFIED (0): The metrics type is unspecified. By default, metrics without a particular specification are for leaf entity types (i.e., top-level entity types without child types, or child types which are not parent types themselves). AGGREGATE (1): Indicates whether metrics for this particular label type represent an aggregate of metrics for other types instead of being based on actual TP/FP/FN values for the label type. Metrics for parent (i.e., non-leaf) entity types are an aggregate of metrics for their children.