Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics
- 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 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::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics>
Metrics for each
confidenceThresholdin 0.00,0.05,0.10,...,0.95,0.96,0.97,0. -
#confusion_matrix ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
-
#log_loss ⇒ Float
The Log Loss metric.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics
constructor
A new instance of GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics
Returns a new instance of GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics.
49413 49414 49415 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49413 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
49386 49387 49388 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49386 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
49392 49393 49394 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49392 def au_roc @au_roc end |
#confidence_metrics ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics>
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
49401 49402 49403 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49401 def confidence_metrics @confidence_metrics end |
#confusion_matrix ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
Corresponds to the JSON property confusionMatrix
49406 49407 49408 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49406 def confusion_matrix @confusion_matrix end |
#log_loss ⇒ Float
The Log Loss metric.
Corresponds to the JSON property logLoss
49411 49412 49413 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49411 def log_loss @log_loss end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
49418 49419 49420 49421 49422 49423 49424 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 49418 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 |