Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics
- 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 classification evaluation results.
Instance Attribute Summary collapse
-
#au_prc ⇒ Float
The Area Under Precision-Recall Curve metric.
-
#au_roc ⇒ Float
The Area Under Receiver Operating Characteristic curve metric.
-
#confidence_metrics ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics>
Metrics for each
confidenceThreshold
in 0.00,0.05,0.10,...,0.95,0.96,0.97,0. -
#confusion_matrix ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
-
#log_loss ⇒ Float
The Log Loss metric.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics
constructor
A new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics
Returns a new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics.
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23201 def initialize(**args) update!(**args) end |
Instance Attribute Details
#au_prc ⇒ Float
The Area Under Precision-Recall Curve metric. Micro-averaged for the overall
evaluation.
Corresponds to the JSON property auPrc
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23174 def au_prc @au_prc end |
#au_roc ⇒ Float
The Area Under Receiver Operating Characteristic curve metric. Micro-averaged
for the overall evaluation.
Corresponds to the JSON property auRoc
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23180 def au_roc @au_roc end |
#confidence_metrics ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics>
Metrics for each confidenceThreshold
in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.
98,0.99 and positionThreshold
= INT32_MAX_VALUE. ROC and precision-recall
curves, and other aggregated metrics are derived from them. The confidence
metrics entries may also be supplied for additional values of
positionThreshold
, but from these no aggregated metrics are computed.
Corresponds to the JSON property confidenceMetrics
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23189 def confidence_metrics @confidence_metrics end |
#confusion_matrix ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
Corresponds to the JSON property confusionMatrix
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23194 def confusion_matrix @confusion_matrix end |
#log_loss ⇒ Float
The Log Loss metric.
Corresponds to the JSON property logLoss
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 23199 def log_loss @log_loss 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 23206 def update!(**args) @au_prc = args[:au_prc] if args.key?(:au_prc) @au_roc = args[:au_roc] if args.key?(:au_roc) @confidence_metrics = args[:confidence_metrics] if args.key?(:confidence_metrics) @confusion_matrix = args[:confusion_matrix] if args.key?(:confusion_matrix) @log_loss = args[:log_loss] if args.key?(:log_loss) end |