Class: Google::Apis::DialogflowV3beta1::GoogleCloudDialogflowCxV3beta1NluSettings

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/dialogflow_v3beta1/classes.rb,
lib/google/apis/dialogflow_v3beta1/representations.rb,
lib/google/apis/dialogflow_v3beta1/representations.rb

Overview

Settings related to NLU.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudDialogflowCxV3beta1NluSettings

Returns a new instance of GoogleCloudDialogflowCxV3beta1NluSettings.



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# File 'lib/google/apis/dialogflow_v3beta1/classes.rb', line 7122

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#classification_threshold ⇒ Float

To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a no-match event will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0. 0, the default of 0.3 is used. Corresponds to the JSON property classificationThreshold

Returns:

  • (Float) 


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# File 'lib/google/apis/dialogflow_v3beta1/classes.rb', line 7110

def classification_threshold
  @classification_threshold
end

#model_training_mode ⇒ String

Indicates NLU model training mode. Corresponds to the JSON property modelTrainingMode

Returns:

  • (String) 


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# File 'lib/google/apis/dialogflow_v3beta1/classes.rb', line 7115

def model_training_mode
  @model_training_mode
end

#model_type ⇒ String

Indicates the type of NLU model. Corresponds to the JSON property modelType

Returns:

  • (String) 


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# File 'lib/google/apis/dialogflow_v3beta1/classes.rb', line 7120

def model_type
  @model_type
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/dialogflow_v3beta1/classes.rb', line 7127

def update!(**args)
  @classification_threshold = args[:classification_threshold] if args.key?(:classification_threshold)
  @model_training_mode = args[:model_training_mode] if args.key?(:model_training_mode)
  @model_type = args[:model_type] if args.key?(:model_type)
end