Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
- 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
Model evaluation metrics for text sentiment problems.
Instance Attribute Summary collapse
-
#confusion_matrix ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix
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) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
constructor
A new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics
Returns a new instance of GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics.
36519 36520 36521 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36519 def initialize(**args) update!(**args) end |
Instance Attribute Details
#confusion_matrix ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix
Confusion matrix of the evaluation. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property confusionMatrix
36478 36479 36480 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36478 def confusion_matrix @confusion_matrix end |
#f1_score ⇒ Float
The harmonic mean of recall and precision.
Corresponds to the JSON property f1Score
36483 36484 36485 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36483 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
36489 36490 36491 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36489 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
36495 36496 36497 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36495 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
36501 36502 36503 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36501 def mean_squared_error @mean_squared_error end |
#precision ⇒ Float
Precision.
Corresponds to the JSON property precision
36506 36507 36508 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36506 def precision @precision end |
#quadratic_kappa ⇒ Float
Quadratic weighted kappa. Only set for ModelEvaluations, not for
ModelEvaluationSlices.
Corresponds to the JSON property quadraticKappa
36512 36513 36514 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36512 def quadratic_kappa @quadratic_kappa end |
#recall ⇒ Float
Recall.
Corresponds to the JSON property recall
36517 36518 36519 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36517 def recall @recall end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
36524 36525 36526 36527 36528 36529 36530 36531 36532 36533 |
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 36524 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 |