Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
- 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
Model evaluation metrics for text sentiment problems.
Instance Attribute Summary collapse
-
#confusion_matrix ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation.
-
#f1_score ⇒ Float
The harmonic mean of recall and precision.
-
#linear_kappa ⇒ Float
Linear weighted kappa.
-
#mean_absolute_error ⇒ Float
Mean absolute error.
-
#mean_squared_error ⇒ Float
Mean squared error.
-
#precision ⇒ Float
Precision.
-
#quadratic_kappa ⇒ Float
Quadratic weighted kappa.
-
#recall ⇒ Float
Recall.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
constructor
A new instance of GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
Returns a new instance of GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics.
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16600 def initialize(**args) update!(**args) end |
Instance Attribute Details
#confusion_matrix ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property confusionMatrix
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16559 def confusion_matrix @confusion_matrix end |
#f1_score ⇒ Float
The harmonic mean of recall and precision.
Corresponds to the JSON property f1Score
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16564 def f1_score @f1_score end |
#linear_kappa ⇒ Float
Linear weighted kappa. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property linearKappa
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16570 def linear_kappa @linear_kappa end |
#mean_absolute_error ⇒ Float
Mean absolute error. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property meanAbsoluteError
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16576 def mean_absolute_error @mean_absolute_error end |
#mean_squared_error ⇒ Float
Mean squared error. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property meanSquaredError
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16582 def mean_squared_error @mean_squared_error end |
#precision ⇒ Float
Precision.
Corresponds to the JSON property precision
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16587 def precision @precision end |
#quadratic_kappa ⇒ Float
Quadratic weighted kappa. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property quadraticKappa
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16593 def quadratic_kappa @quadratic_kappa end |
#recall ⇒ Float
Recall.
Corresponds to the JSON property recall
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16598 def recall @recall end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16605 def update!(**args) @confusion_matrix = args[:confusion_matrix] if args.key?(:confusion_matrix) @f1_score = args[:f1_score] if args.key?(:f1_score) @linear_kappa = args[:linear_kappa] if args.key?(:linear_kappa) @mean_absolute_error = args[:mean_absolute_error] if args.key?(:mean_absolute_error) @mean_squared_error = args[:mean_squared_error] if args.key?(:mean_squared_error) @precision = args[:precision] if args.key?(:precision) @quadratic_kappa = args[:quadratic_kappa] if args.key?(:quadratic_kappa) @recall = args[:recall] if args.key?(:recall) end |