Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

Metrics for regression evaluation results.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics

Returns a new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics.



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19077

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

Instance Attribute Details

#mean_absolute_error ⇒ Float

Mean Absolute Error (MAE). Corresponds to the JSON property meanAbsoluteError

Returns:

  • (Float) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19052

def mean_absolute_error
  @mean_absolute_error
end

#mean_absolute_percentage_error ⇒ Float

Mean absolute percentage error. Infinity when there are zeros in the ground truth. Corresponds to the JSON property meanAbsolutePercentageError

Returns:

  • (Float) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19058

def mean_absolute_percentage_error
  @mean_absolute_percentage_error
end

#r_squared ⇒ Float

Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant. Corresponds to the JSON property rSquared

Returns:

  • (Float) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19064

def r_squared
  @r_squared
end

#root_mean_squared_error ⇒ Float

Root Mean Squared Error (RMSE). Corresponds to the JSON property rootMeanSquaredError

Returns:

  • (Float) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19069

def root_mean_squared_error
  @root_mean_squared_error
end

#root_mean_squared_log_error ⇒ Float

Root mean squared log error. Undefined when there are negative ground truth values or predictions. Corresponds to the JSON property rootMeanSquaredLogError

Returns:

  • (Float) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19075

def root_mean_squared_log_error
  @root_mean_squared_log_error
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19082

def update!(**args)
  @mean_absolute_error = args[:mean_absolute_error] if args.key?(:mean_absolute_error)
  @mean_absolute_percentage_error = args[:mean_absolute_percentage_error] if args.key?(:mean_absolute_percentage_error)
  @r_squared = args[:r_squared] if args.key?(:r_squared)
  @root_mean_squared_error = args[:root_mean_squared_error] if args.key?(:root_mean_squared_error)
  @root_mean_squared_log_error = args[:root_mean_squared_log_error] if args.key?(:root_mean_squared_log_error)
end