Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics (v0.11.1)

Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics.

Model evaluation metrics for text sentiment problems.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#annotation_spec_id

def annotation_spec_id() -> ::Array<::String>
Returns
  • (::Array<::String>) — Output only. The annotation spec ids used for this evaluation. Deprecated .

#annotation_spec_id=

def annotation_spec_id=(value) -> ::Array<::String>
Parameter
  • value (::Array<::String>) — Output only. The annotation spec ids used for this evaluation. Deprecated .
Returns
  • (::Array<::String>) — Output only. The annotation spec ids used for this evaluation. Deprecated .

#confusion_matrix

def confusion_matrix() -> ::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix
Returns

#confusion_matrix=

def confusion_matrix=(value) -> ::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix
Parameter
Returns

#f1_score

def f1_score() -> ::Float
Returns
  • (::Float) — Output only. The harmonic mean of recall and precision.

#f1_score=

def f1_score=(value) -> ::Float
Parameter
  • value (::Float) — Output only. The harmonic mean of recall and precision.
Returns
  • (::Float) — Output only. The harmonic mean of recall and precision.

#linear_kappa

def linear_kappa() -> ::Float
Returns
  • (::Float) — Output only. Linear weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#linear_kappa=

def linear_kappa=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Linear weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
Returns
  • (::Float) — Output only. Linear weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#mean_absolute_error

def mean_absolute_error() -> ::Float
Returns
  • (::Float) — Output only. Mean absolute error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#mean_absolute_error=

def mean_absolute_error=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Mean absolute error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
Returns
  • (::Float) — Output only. Mean absolute error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#mean_squared_error

def mean_squared_error() -> ::Float
Returns
  • (::Float) — Output only. Mean squared error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#mean_squared_error=

def mean_squared_error=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Mean squared error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
Returns
  • (::Float) — Output only. Mean squared error. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#precision

def precision() -> ::Float
Returns
  • (::Float) — Output only. Precision.

#precision=

def precision=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Precision.
Returns
  • (::Float) — Output only. Precision.

#quadratic_kappa

def quadratic_kappa() -> ::Float
Returns
  • (::Float) — Output only. Quadratic weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#quadratic_kappa=

def quadratic_kappa=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Quadratic weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
Returns
  • (::Float) — Output only. Quadratic weighted kappa. Only set for the overall model evaluation, not for evaluation of a single annotation spec.

#recall

def recall() -> ::Float
Returns
  • (::Float) — Output only. Recall.

#recall=

def recall=(value) -> ::Float
Parameter
  • value (::Float) — Output only. Recall.
Returns
  • (::Float) — Output only. Recall.