Reference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::ModelEvaluation.
Evaluation results of a model.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#annotation_spec_id
def annotation_spec_id() -> ::String Returns
- (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] the display_name field is used.
#annotation_spec_id=
def annotation_spec_id=(value) -> ::String Parameter
- value (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] the display_name field is used.
Returns
- (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] the display_name field is used.
#classification_evaluation_metrics
def classification_evaluation_metrics() -> ::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics Returns
- (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.
#classification_evaluation_metrics=
def classification_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics Parameter
- value (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.
Returns
- (::Google::Cloud::AutoML::V1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.
#create_time
def create_time() -> ::Google::Protobuf::Timestamp Returns
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.
#create_time=
def create_time=(value) -> ::Google::Protobuf::Timestamp Parameter
- value (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.
Returns
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.
#display_name
def display_name() -> ::String Returns
- (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.
#display_name=
def display_name=(value) -> ::String Parameter
- value (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.
Returns
- (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.
#evaluated_example_count
def evaluated_example_count() -> ::Integer Returns
- (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the annotation_spec_id.
#evaluated_example_count=
def evaluated_example_count=(value) -> ::Integer Parameter
- value (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the annotation_spec_id.
Returns
- (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the annotation_spec_id.
#image_object_detection_evaluation_metrics
def image_object_detection_evaluation_metrics() -> ::Google::Cloud::AutoML::V1::ImageObjectDetectionEvaluationMetrics Returns
- (::Google::Cloud::AutoML::V1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.
#image_object_detection_evaluation_metrics=
def image_object_detection_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1::ImageObjectDetectionEvaluationMetrics Parameter
- value (::Google::Cloud::AutoML::V1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.
Returns
- (::Google::Cloud::AutoML::V1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.
#name
def name() -> ::String Returns
- (::String) — Output only. Resource name of the model evaluation. Format:
projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}
#name=
def name=(value) -> ::String Parameter
- value (::String) — Output only. Resource name of the model evaluation. Format:
projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}
Returns
- (::String) — Output only. Resource name of the model evaluation. Format:
projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}
#text_extraction_evaluation_metrics
def text_extraction_evaluation_metrics() -> ::Google::Cloud::AutoML::V1::TextExtractionEvaluationMetrics Returns
- (::Google::Cloud::AutoML::V1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.
#text_extraction_evaluation_metrics=
def text_extraction_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1::TextExtractionEvaluationMetrics Parameter
- value (::Google::Cloud::AutoML::V1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.
Returns
- (::Google::Cloud::AutoML::V1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.
#text_sentiment_evaluation_metrics
def text_sentiment_evaluation_metrics() -> ::Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics Returns
- (::Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.
#text_sentiment_evaluation_metrics=
def text_sentiment_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics Parameter
- value (::Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.
Returns
- (::Google::Cloud::AutoML::V1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.
#translation_evaluation_metrics
def translation_evaluation_metrics() -> ::Google::Cloud::AutoML::V1::TranslationEvaluationMetrics Returns
- (::Google::Cloud::AutoML::V1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.
#translation_evaluation_metrics=
def translation_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1::TranslationEvaluationMetrics Parameter
- value (::Google::Cloud::AutoML::V1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.
Returns
- (::Google::Cloud::AutoML::V1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.