Class: Google::Apis::BigqueryV2::EvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::BigqueryV2::EvaluationMetrics
- Includes:
- Core::Hashable, Core::JsonObjectSupport
- Defined in:
- lib/google/apis/bigquery_v2/classes.rb,
lib/google/apis/bigquery_v2/representations.rb,
lib/google/apis/bigquery_v2/representations.rb
Overview
Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.
Instance Attribute Summary collapse
-
#arima_forecasting_metrics ⇒ Google::Apis::BigqueryV2::ArimaForecastingMetrics
Model evaluation metrics for ARIMA forecasting models.
-
#binary_classification_metrics ⇒ Google::Apis::BigqueryV2::BinaryClassificationMetrics
Evaluation metrics for binary classification/classifier models.
-
#clustering_metrics ⇒ Google::Apis::BigqueryV2::ClusteringMetrics
Evaluation metrics for clustering models.
-
#multi_class_classification_metrics ⇒ Google::Apis::BigqueryV2::MultiClassClassificationMetrics
Evaluation metrics for multi-class classification/classifier models.
-
#ranking_metrics ⇒ Google::Apis::BigqueryV2::RankingMetrics
Evaluation metrics used by weighted-ALS models specified by feedback_type= implicit.
-
#regression_metrics ⇒ Google::Apis::BigqueryV2::RegressionMetrics
Evaluation metrics for regression and explicit feedback type matrix factorization models.
Instance Method Summary collapse
-
#initialize(**args) ⇒ EvaluationMetrics
constructor
A new instance of EvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ EvaluationMetrics
Returns a new instance of EvaluationMetrics.
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2096 def initialize(**args) update!(**args) end |
Instance Attribute Details
#arima_forecasting_metrics ⇒ Google::Apis::BigqueryV2::ArimaForecastingMetrics
Model evaluation metrics for ARIMA forecasting models.
Corresponds to the JSON property arimaForecastingMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2067 def arima_forecasting_metrics @arima_forecasting_metrics end |
#binary_classification_metrics ⇒ Google::Apis::BigqueryV2::BinaryClassificationMetrics
Evaluation metrics for binary classification/classifier models.
Corresponds to the JSON property binaryClassificationMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2072 def binary_classification_metrics @binary_classification_metrics end |
#clustering_metrics ⇒ Google::Apis::BigqueryV2::ClusteringMetrics
Evaluation metrics for clustering models.
Corresponds to the JSON property clusteringMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2077 def clustering_metrics @clustering_metrics end |
#multi_class_classification_metrics ⇒ Google::Apis::BigqueryV2::MultiClassClassificationMetrics
Evaluation metrics for multi-class classification/classifier models.
Corresponds to the JSON property multiClassClassificationMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2082 def multi_class_classification_metrics @multi_class_classification_metrics end |
#ranking_metrics ⇒ Google::Apis::BigqueryV2::RankingMetrics
Evaluation metrics used by weighted-ALS models specified by feedback_type=
implicit.
Corresponds to the JSON property rankingMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2088 def ranking_metrics @ranking_metrics end |
#regression_metrics ⇒ Google::Apis::BigqueryV2::RegressionMetrics
Evaluation metrics for regression and explicit feedback type matrix
factorization models.
Corresponds to the JSON property regressionMetrics
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2094 def regression_metrics @regression_metrics end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/bigquery_v2/classes.rb', line 2101 def update!(**args) @arima_forecasting_metrics = args[:arima_forecasting_metrics] if args.key?(:arima_forecasting_metrics) @binary_classification_metrics = args[:binary_classification_metrics] if args.key?(:binary_classification_metrics) @clustering_metrics = args[:clustering_metrics] if args.key?(:clustering_metrics) @multi_class_classification_metrics = args[:multi_class_classification_metrics] if args.key?(:multi_class_classification_metrics) @ranking_metrics = args[:ranking_metrics] if args.key?(:ranking_metrics) @regression_metrics = args[:regression_metrics] if args.key?(:regression_metrics) end |