Class: Aws::Comprehend::Types::EntityRecognizerEvaluationMetrics

Inherits:
Struct
  • Object
show all
Defined in:
gems/aws-sdk-comprehend/lib/aws-sdk-comprehend/types.rb

Overview

Detailed information about the accuracy of an entity recognizer.

See Also:

Constant Summary collapse

SENSITIVE = 
[]

Instance Attribute Summary collapse

Instance Attribute Details

#f1_score ⇒ Float

A measure of how accurate the recognizer results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.

Returns:

  • (Float) 


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# File 'gems/aws-sdk-comprehend/lib/aws-sdk-comprehend/types.rb', line 3265

class EntityRecognizerEvaluationMetrics < Struct.new(
  :precision,
  :recall,
  :f1_score)
  SENSITIVE = []
  include Aws::Structure
end

#precision ⇒ Float

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

Returns:

  • (Float) 


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# File 'gems/aws-sdk-comprehend/lib/aws-sdk-comprehend/types.rb', line 3265

class EntityRecognizerEvaluationMetrics < Struct.new(
  :precision,
  :recall,
  :f1_score)
  SENSITIVE = []
  include Aws::Structure
end

#recall ⇒ Float

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

Returns:

  • (Float) 


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# File 'gems/aws-sdk-comprehend/lib/aws-sdk-comprehend/types.rb', line 3265

class EntityRecognizerEvaluationMetrics < Struct.new(
  :precision,
  :recall,
  :f1_score)
  SENSITIVE = []
  include Aws::Structure
end