Class: Google::Apis::LanguageV2::XpsEvaluationMetrics

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/language_v2/classes.rb,
lib/google/apis/language_v2/representations.rb,
lib/google/apis/language_v2/representations.rb

Overview

Contains xPS-specific model evaluation metrics either for a single annotation spec (label), or for the model overall. Next tag: 18.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ XpsEvaluationMetrics

Returns a new instance of XpsEvaluationMetrics.



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# File 'lib/google/apis/language_v2/classes.rb', line 1981

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

Instance Attribute Details

#annotation_spec_id_token ⇒ String

The annotation_spec for which this evaluation metrics instance had been created. Empty iff this is an overall model evaluation (like Tables evaluation metrics), i.e. aggregated across all labels. The value comes from the input annotations in AnnotatedExample. For MVP product or for text sentiment models where annotation_spec_id_token is not available, set label instead. Corresponds to the JSON property annotationSpecIdToken

Returns:

  • (String) 


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# File 'lib/google/apis/language_v2/classes.rb', line 1886

def annotation_spec_id_token
  @annotation_spec_id_token
end

#category ⇒ Fixnum

The integer category label for which this evaluation metric instance had been created. Valid categories are 0 or higher. Overall model evaluation should set this to negative values (rather than implicit zero). Only used for Image Segmentation (prefer to set annotation_spec_id_token instead). Note: uCAIP Image Segmentation should use annotation_spec_id_token. Corresponds to the JSON property category

Returns:

  • (Fixnum) 


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# File 'lib/google/apis/language_v2/classes.rb', line 1895

def category
  @category
end

#evaluated_example_count ⇒ Fixnum

The number of examples used to create this evaluation metrics instance. Corresponds to the JSON property evaluatedExampleCount

Returns:

  • (Fixnum) 


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# File 'lib/google/apis/language_v2/classes.rb', line 1900

def evaluated_example_count
  @evaluated_example_count
end

#image_classification_eval_metrics ⇒ Google::Apis::LanguageV2::XpsClassificationEvaluationMetrics

Model evaluation metrics for classification problems. It can be used for image and video classification. Next tag: 9. Corresponds to the JSON property imageClassificationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1906

def image_classification_eval_metrics
  @image_classification_eval_metrics
end

#image_object_detection_eval_metrics ⇒ Google::Apis::LanguageV2::XpsImageObjectDetectionEvaluationMetrics

Model evaluation metrics for image object detection problems. Evaluates prediction quality of labeled bounding boxes. Corresponds to the JSON property imageObjectDetectionEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1912

def image_object_detection_eval_metrics
  @image_object_detection_eval_metrics
end

#image_segmentation_eval_metrics ⇒ Google::Apis::LanguageV2::XpsImageSegmentationEvaluationMetrics

Model evaluation metrics for image segmentation problems. Next tag: 4. Corresponds to the JSON property imageSegmentationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1917

def image_segmentation_eval_metrics
  @image_segmentation_eval_metrics
end

#label ⇒ String

The label for which this evaluation metrics instance had been created. Empty iff this is an overall model evaluation (like Tables evaluation metrics), i.e. aggregated across all labels. The label maps to AnnotationSpec.display_name in Public API protos. Only used by MVP implementation and text sentiment FULL implementation. Corresponds to the JSON property label

Returns:

  • (String) 


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# File 'lib/google/apis/language_v2/classes.rb', line 1926

def label
  @label
end

#regression_eval_metrics ⇒ Google::Apis::LanguageV2::XpsRegressionEvaluationMetrics

Model evaluation metrics for regression problems. It can be used for Tables. Corresponds to the JSON property regressionEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1931

def regression_eval_metrics
  @regression_eval_metrics
end

#tables_classification_eval_metrics ⇒ Google::Apis::LanguageV2::XpsClassificationEvaluationMetrics

Model evaluation metrics for classification problems. It can be used for image and video classification. Next tag: 9. Corresponds to the JSON property tablesClassificationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1937

def tables_classification_eval_metrics
  @tables_classification_eval_metrics
end

#tables_eval_metrics ⇒ Google::Apis::LanguageV2::XpsTablesEvaluationMetrics

Corresponds to the JSON property tablesEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1942

def tables_eval_metrics
  @tables_eval_metrics
end

#text_classification_eval_metrics ⇒ Google::Apis::LanguageV2::XpsClassificationEvaluationMetrics

Model evaluation metrics for classification problems. It can be used for image and video classification. Next tag: 9. Corresponds to the JSON property textClassificationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1948

def text_classification_eval_metrics
  @text_classification_eval_metrics
end

#text_extraction_eval_metrics ⇒ Google::Apis::LanguageV2::XpsTextExtractionEvaluationMetrics

Corresponds to the JSON property textExtractionEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1953

def text_extraction_eval_metrics
  @text_extraction_eval_metrics
end

#text_sentiment_eval_metrics ⇒ Google::Apis::LanguageV2::XpsTextSentimentEvaluationMetrics

Model evaluation metrics for text sentiment problems. Corresponds to the JSON property textSentimentEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1958

def text_sentiment_eval_metrics
  @text_sentiment_eval_metrics
end

#translation_eval_metrics ⇒ Google::Apis::LanguageV2::XpsTranslationEvaluationMetrics

Evaluation metrics for the dataset. Corresponds to the JSON property translationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1963

def translation_eval_metrics
  @translation_eval_metrics
end

#video_action_recognition_eval_metrics ⇒ Google::Apis::LanguageV2::XpsVideoActionRecognitionEvaluationMetrics

Model evaluation metrics for video action recognition. Corresponds to the JSON property videoActionRecognitionEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1968

def video_action_recognition_eval_metrics
  @video_action_recognition_eval_metrics
end

#video_classification_eval_metrics ⇒ Google::Apis::LanguageV2::XpsClassificationEvaluationMetrics

Model evaluation metrics for classification problems. It can be used for image and video classification. Next tag: 9. Corresponds to the JSON property videoClassificationEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1974

def video_classification_eval_metrics
  @video_classification_eval_metrics
end

#video_object_tracking_eval_metrics ⇒ Google::Apis::LanguageV2::XpsVideoObjectTrackingEvaluationMetrics

Model evaluation metrics for ObjectTracking problems. Next tag: 10. Corresponds to the JSON property videoObjectTrackingEvalMetrics

Returns:



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# File 'lib/google/apis/language_v2/classes.rb', line 1979

def video_object_tracking_eval_metrics
  @video_object_tracking_eval_metrics
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/language_v2/classes.rb', line 1986

def update!(**args)
  @annotation_spec_id_token = args[:annotation_spec_id_token] if args.key?(:annotation_spec_id_token)
  @category = args[:category] if args.key?(:category)
  @evaluated_example_count = args[:evaluated_example_count] if args.key?(:evaluated_example_count)
  @image_classification_eval_metrics = args[:image_classification_eval_metrics] if args.key?(:image_classification_eval_metrics)
  @image_object_detection_eval_metrics = args[:image_object_detection_eval_metrics] if args.key?(:image_object_detection_eval_metrics)
  @image_segmentation_eval_metrics = args[:image_segmentation_eval_metrics] if args.key?(:image_segmentation_eval_metrics)
  @label = args[:label] if args.key?(:label)
  @regression_eval_metrics = args[:regression_eval_metrics] if args.key?(:regression_eval_metrics)
  @tables_classification_eval_metrics = args[:tables_classification_eval_metrics] if args.key?(:tables_classification_eval_metrics)
  @tables_eval_metrics = args[:tables_eval_metrics] if args.key?(:tables_eval_metrics)
  @text_classification_eval_metrics = args[:text_classification_eval_metrics] if args.key?(:text_classification_eval_metrics)
  @text_extraction_eval_metrics = args[:text_extraction_eval_metrics] if args.key?(:text_extraction_eval_metrics)
  @text_sentiment_eval_metrics = args[:text_sentiment_eval_metrics] if args.key?(:text_sentiment_eval_metrics)
  @translation_eval_metrics = args[:translation_eval_metrics] if args.key?(:translation_eval_metrics)
  @video_action_recognition_eval_metrics = args[:video_action_recognition_eval_metrics] if args.key?(:video_action_recognition_eval_metrics)
  @video_classification_eval_metrics = args[:video_classification_eval_metrics] if args.key?(:video_classification_eval_metrics)
  @video_object_tracking_eval_metrics = args[:video_object_tracking_eval_metrics] if args.key?(:video_object_tracking_eval_metrics)
end