Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

Metrics for regression evaluation results.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics

Returns a new instance of GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics.



17946
17947
17948
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17946

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

Instance Attribute Details

#mean_absolute_errorFloat

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

Returns:

  • (Float)


17921
17922
17923
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17921

def mean_absolute_error
  @mean_absolute_error
end

#mean_absolute_percentage_errorFloat

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

Returns:

  • (Float)


17927
17928
17929
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17927

def mean_absolute_percentage_error
  @mean_absolute_percentage_error
end

#r_squaredFloat

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)


17933
17934
17935
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17933

def r_squared
  @r_squared
end

#root_mean_squared_errorFloat

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

Returns:

  • (Float)


17938
17939
17940
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17938

def root_mean_squared_error
  @root_mean_squared_error
end

#root_mean_squared_log_errorFloat

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

Returns:

  • (Float)


17944
17945
17946
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17944

def root_mean_squared_log_error
  @root_mean_squared_log_error
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



17951
17952
17953
17954
17955
17956
17957
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17951

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