Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics
- 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
-
#mean_absolute_error ⇒ Float
Mean Absolute Error (MAE).
-
#mean_absolute_percentage_error ⇒ Float
Mean absolute percentage error.
-
#quantile_metrics ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry>
The quantile metrics entries for each quantile.
-
#r_squared ⇒ Float
Coefficient of determination as Pearson correlation coefficient.
-
#root_mean_squared_error ⇒ Float
Root Mean Squared Error (RMSE).
-
#root_mean_squared_log_error ⇒ Float
Root mean squared log error.
-
#root_mean_squared_percentage_error ⇒ Float
Root Mean Square Percentage Error.
-
#weighted_absolute_percentage_error ⇒ Float
Weighted Absolute Percentage Error.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics
constructor
A new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics
Returns a new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics.
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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_error ⇒ Float
Mean Absolute Error (MAE).
Corresponds to the JSON property meanAbsoluteError
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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_error ⇒ Float
Mean absolute percentage error. Infinity when there are zeros in the ground
truth.
Corresponds to the JSON property meanAbsolutePercentageError
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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_metrics ⇒ Array<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_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
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22197 def r_squared @r_squared end |
#root_mean_squared_error ⇒ Float
Root Mean Squared Error (RMSE).
Corresponds to the JSON property rootMeanSquaredError
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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_error ⇒ Float
Root mean squared log error. Undefined when there are negative ground truth
values or predictions.
Corresponds to the JSON property rootMeanSquaredLogError
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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_error ⇒ Float
Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary
when MSPE is negative.
Corresponds to the JSON property rootMeanSquaredPercentageError
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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_error ⇒ Float
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
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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
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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 |