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.
19488 19489 19490 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19488 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
19461 19462 19463 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19461 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
19467 19468 19469 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19467 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
19476 19477 19478 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19476 def confidence_metrics @confidence_metrics end |
#confusion_matrix ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
Corresponds to the JSON property confusionMatrix
19481 19482 19483 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19481 def confusion_matrix @confusion_matrix end |
#log_loss ⇒ Float
The Log Loss metric.
Corresponds to the JSON property logLoss
19486 19487 19488 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19486 def log_loss @log_loss end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
19493 19494 19495 19496 19497 19498 19499 |
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 19493 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 |