Class: Aws::Comprehend::Types::EntityTypesEvaluationMetrics

Inherits:

Struct

• Object
• Struct
• Aws::Comprehend::Types::EntityTypesEvaluationMetrics

Defined in:

(unknown)

Overview

Detailed information about the accuracy of an entity recognizer for a specific entity type.

Returned by:

• Aws::Comprehend::Types::EntityRecognizerMetadataEntityTypesListItem#evaluation_metrics

See Also:

• AWS API Documentation

Instance Attribute Summary

• #f1_score ⇒ Float

  A measure of how accurate the recognizer results are for for a specific entity type in the test data.

• #precision ⇒ Float

  A measure of the usefulness of the recognizer results for a specific entity type in the test data.

• #recall ⇒ Float

  A measure of how complete the recognizer results are for a specific entity type in the test data.

Instance Attribute Details

#f1_score ⇒ Float

A measure of how accurate the recognizer results are for for a specific entity type in the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. The highest score is 1, and the worst score is 0.

Returns:

• (Float) —

  A measure of how accurate the recognizer results are for for a specific entity type in the test data.

#precision ⇒ Float

A measure of the usefulness of the recognizer results for a specific entity type in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.

Returns:

• (Float) —

  A measure of the usefulness of the recognizer results for a specific entity type in the test data.

#recall ⇒ Float

A measure of how complete the recognizer results are for a specific entity type in the test data. High recall means that the recognizer returned most of the relevant results.

Returns:

• (Float) —

  A measure of how complete the recognizer results are for a specific entity type in the test data.