Reference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics.
Model evaluation metrics for text sentiment problems.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#confusion_matrix
def confusion_matrix() -> ::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics::ConfusionMatrix
Returns
- (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics::ConfusionMatrix) — Output only. Confusion matrix of the evaluation. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
#confusion_matrix=
def confusion_matrix=(value) -> ::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics::ConfusionMatrix
Parameter
- value (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics::ConfusionMatrix) — Output only. Confusion matrix of the evaluation. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
Returns
- (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics::ConfusionMatrix) — Output only. Confusion matrix of the evaluation. Only set for the overall model evaluation, not for evaluation of a single annotation spec.
#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.