Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics

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
more...

Overview

Metrics for forecasting evaluation results.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics

Returns a new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics.

[View source]

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22223

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

Instance Attribute Details

#mean_absolute_errorFloat

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 22180

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)

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22186

def mean_absolute_percentage_error
  @mean_absolute_percentage_error
end

#quantile_metricsArray<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry>

The quantile metrics entries for each quantile. Corresponds to the JSON property quantileMetrics


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22191

def quantile_metrics
  @quantile_metrics
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)

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22197

def r_squared
  @r_squared
end

#root_mean_squared_errorFloat

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 22202

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)

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22208

def root_mean_squared_log_error
  @root_mean_squared_log_error
end

#root_mean_squared_percentage_errorFloat

Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative. Corresponds to the JSON property rootMeanSquaredPercentageError

Returns:

  • (Float)

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22214

def root_mean_squared_percentage_error
  @root_mean_squared_percentage_error
end

#weighted_absolute_percentage_errorFloat

Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number. Corresponds to the JSON property weightedAbsolutePercentageError

Returns:

  • (Float)

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22221

def weighted_absolute_percentage_error
  @weighted_absolute_percentage_error
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object

[View source]

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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22228

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)
  @quantile_metrics = args[:quantile_metrics] if args.key?(:quantile_metrics)
  @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)
  @root_mean_squared_percentage_error = args[:root_mean_squared_percentage_error] if args.key?(:root_mean_squared_percentage_error)
  @weighted_absolute_percentage_error = args[:weighted_absolute_percentage_error] if args.key?(:weighted_absolute_percentage_error)
end