Interface ModelEvaluationOrBuilder (2.3.5)

Version 2.3.5

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public interface ModelEvaluationOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getAnnotationSpecId()

public abstract String getAnnotationSpecId()

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 the display_name field is used.

string annotation_spec_id = 2;

Returns

Type	Description
String	The annotationSpecId.

getAnnotationSpecIdBytes()

public abstract ByteString getAnnotationSpecIdBytes()

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 the display_name field is used.

string annotation_spec_id = 2;

Returns

Type	Description
ByteString	The bytes for annotationSpecId.

getClassificationEvaluationMetrics()

public abstract ClassificationProto.ClassificationEvaluationMetrics getClassificationEvaluationMetrics()

Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics classification_evaluation_metrics = 8;

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics	The classificationEvaluationMetrics.

getClassificationEvaluationMetricsOrBuilder()

public abstract ClassificationProto.ClassificationEvaluationMetricsOrBuilder getClassificationEvaluationMetricsOrBuilder()

Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics classification_evaluation_metrics = 8;

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetricsOrBuilder

getCreateTime()

public abstract Timestamp getCreateTime()

Output only. Timestamp when this model evaluation was created.

.google.protobuf.Timestamp create_time = 5;

Returns

Type	Description
Timestamp	The createTime.

getCreateTimeOrBuilder()

public abstract TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Timestamp when this model evaluation was created.

.google.protobuf.Timestamp create_time = 5;

Returns

Type	Description
TimestampOrBuilder

getDisplayName()

public abstract String getDisplayName()

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 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.

string display_name = 15;

Returns

Type	Description
String	The displayName.

getDisplayNameBytes()

public abstract ByteString getDisplayNameBytes()

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 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.

string display_name = 15;

Returns

Type	Description
ByteString	The bytes for displayName.

getEvaluatedExampleCount()

public abstract int getEvaluatedExampleCount()

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.

int32 evaluated_example_count = 6;

Returns

Type	Description
int	The evaluatedExampleCount.

getImageObjectDetectionEvaluationMetrics()

public abstract ImageObjectDetectionEvaluationMetrics getImageObjectDetectionEvaluationMetrics()

Model evaluation metrics for image object detection.

.google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;

Returns

Type	Description
ImageObjectDetectionEvaluationMetrics	The imageObjectDetectionEvaluationMetrics.

getImageObjectDetectionEvaluationMetricsOrBuilder()

public abstract ImageObjectDetectionEvaluationMetricsOrBuilder getImageObjectDetectionEvaluationMetricsOrBuilder()

Model evaluation metrics for image object detection.

.google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;

Returns

Type	Description
ImageObjectDetectionEvaluationMetricsOrBuilder

getMetricsCase()

public abstract ModelEvaluation.MetricsCase getMetricsCase()

Returns

Type	Description
ModelEvaluation.MetricsCase

getName()

public abstract String getName()

Output only. Resource name of the model evaluation. Format: projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

string name = 1;

Returns

Type	Description
String	The name.

getNameBytes()

public abstract ByteString getNameBytes()

Output only. Resource name of the model evaluation. Format: projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

string name = 1;

Returns

Type	Description
ByteString	The bytes for name.

getRegressionEvaluationMetrics()

public abstract RegressionProto.RegressionEvaluationMetrics getRegressionEvaluationMetrics()

Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

.google.cloud.automl.v1beta1.RegressionEvaluationMetrics regression_evaluation_metrics = 24;

Returns

Type	Description
RegressionProto.RegressionEvaluationMetrics	The regressionEvaluationMetrics.

getRegressionEvaluationMetricsOrBuilder()

public abstract RegressionProto.RegressionEvaluationMetricsOrBuilder getRegressionEvaluationMetricsOrBuilder()

Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

.google.cloud.automl.v1beta1.RegressionEvaluationMetrics regression_evaluation_metrics = 24;

Returns

Type	Description
RegressionProto.RegressionEvaluationMetricsOrBuilder

getTextExtractionEvaluationMetrics()

public abstract TextExtractionEvaluationMetrics getTextExtractionEvaluationMetrics()

Evaluation metrics for text extraction models.

.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;

Returns

Type	Description
TextExtractionEvaluationMetrics	The textExtractionEvaluationMetrics.

getTextExtractionEvaluationMetricsOrBuilder()

public abstract TextExtractionEvaluationMetricsOrBuilder getTextExtractionEvaluationMetricsOrBuilder()

Evaluation metrics for text extraction models.

.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;

Returns

Type	Description
TextExtractionEvaluationMetricsOrBuilder

getTextSentimentEvaluationMetrics()

public abstract TextSentimentProto.TextSentimentEvaluationMetrics getTextSentimentEvaluationMetrics()

Evaluation metrics for text sentiment models.

.google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;

Returns

Type	Description
TextSentimentProto.TextSentimentEvaluationMetrics	The textSentimentEvaluationMetrics.

getTextSentimentEvaluationMetricsOrBuilder()

public abstract TextSentimentProto.TextSentimentEvaluationMetricsOrBuilder getTextSentimentEvaluationMetricsOrBuilder()

Evaluation metrics for text sentiment models.

.google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;

Returns

Type	Description
TextSentimentProto.TextSentimentEvaluationMetricsOrBuilder

getTranslationEvaluationMetrics()

public abstract TranslationEvaluationMetrics getTranslationEvaluationMetrics()

Model evaluation metrics for translation.

.google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;

Returns

Type	Description
TranslationEvaluationMetrics	The translationEvaluationMetrics.

getTranslationEvaluationMetricsOrBuilder()

public abstract TranslationEvaluationMetricsOrBuilder getTranslationEvaluationMetricsOrBuilder()

Model evaluation metrics for translation.

.google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;

Returns

Type	Description
TranslationEvaluationMetricsOrBuilder

getVideoObjectTrackingEvaluationMetrics()

public abstract VideoObjectTrackingEvaluationMetrics getVideoObjectTrackingEvaluationMetrics()

Model evaluation metrics for video object tracking.

.google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;

Returns

Type	Description
VideoObjectTrackingEvaluationMetrics	The videoObjectTrackingEvaluationMetrics.

getVideoObjectTrackingEvaluationMetricsOrBuilder()

public abstract VideoObjectTrackingEvaluationMetricsOrBuilder getVideoObjectTrackingEvaluationMetricsOrBuilder()

Model evaluation metrics for video object tracking.

.google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;

Returns

Type	Description
VideoObjectTrackingEvaluationMetricsOrBuilder

hasClassificationEvaluationMetrics()

public abstract boolean hasClassificationEvaluationMetrics()

Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics classification_evaluation_metrics = 8;

Returns

Type	Description
boolean	Whether the classificationEvaluationMetrics field is set.

hasCreateTime()

public abstract boolean hasCreateTime()

Output only. Timestamp when this model evaluation was created.

.google.protobuf.Timestamp create_time = 5;

Returns

Type	Description
boolean	Whether the createTime field is set.

hasImageObjectDetectionEvaluationMetrics()

public abstract boolean hasImageObjectDetectionEvaluationMetrics()

Model evaluation metrics for image object detection.

.google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;

Returns

Type	Description
boolean	Whether the imageObjectDetectionEvaluationMetrics field is set.

hasRegressionEvaluationMetrics()

public abstract boolean hasRegressionEvaluationMetrics()

Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

.google.cloud.automl.v1beta1.RegressionEvaluationMetrics regression_evaluation_metrics = 24;

Returns

Type	Description
boolean	Whether the regressionEvaluationMetrics field is set.

hasTextExtractionEvaluationMetrics()

public abstract boolean hasTextExtractionEvaluationMetrics()

Evaluation metrics for text extraction models.

.google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;

Returns

Type	Description
boolean	Whether the textExtractionEvaluationMetrics field is set.

hasTextSentimentEvaluationMetrics()

public abstract boolean hasTextSentimentEvaluationMetrics()

Evaluation metrics for text sentiment models.

.google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;

Returns

Type	Description
boolean	Whether the textSentimentEvaluationMetrics field is set.

hasTranslationEvaluationMetrics()

public abstract boolean hasTranslationEvaluationMetrics()

Model evaluation metrics for translation.

.google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;

Returns

Type	Description
boolean	Whether the translationEvaluationMetrics field is set.

hasVideoObjectTrackingEvaluationMetrics()

public abstract boolean hasVideoObjectTrackingEvaluationMetrics()

Model evaluation metrics for video object tracking.

.google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;

Returns

Type	Description
boolean	Whether the videoObjectTrackingEvaluationMetrics field is set.