Class: Aws::Comprehend::Types::EntityTypesEvaluationMetrics
- Inherits:
-
Struct
- Object
- Struct
- Aws::Comprehend::Types::EntityTypesEvaluationMetrics
- Includes:
- Structure
- Defined in:
- lib/aws-sdk-comprehend/types.rb
Overview
Detailed information about the accuracy of an entity recognizer for a specific entity type.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#f1_score ⇒ Float
A measure of how accurate the recognizer results are 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 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.
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# File 'lib/aws-sdk-comprehend/types.rb', line 4459 class EntityTypesEvaluationMetrics < Struct.new( :precision, :recall, :f1_score) SENSITIVE = [] include Aws::Structure end |
#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.
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# File 'lib/aws-sdk-comprehend/types.rb', line 4459 class EntityTypesEvaluationMetrics < Struct.new( :precision, :recall, :f1_score) SENSITIVE = [] include Aws::Structure end |
#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.
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# File 'lib/aws-sdk-comprehend/types.rb', line 4459 class EntityTypesEvaluationMetrics < Struct.new( :precision, :recall, :f1_score) SENSITIVE = [] include Aws::Structure end |