Package com.google.cloud.automl.v1beta1

Interface ModelEvaluationOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    ModelEvaluation, ModelEvaluation.Builder
    public interface ModelEvaluationOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • hasClassificationEvaluationMetrics

        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:
        Whether the classificationEvaluationMetrics field is set.

      • getClassificationEvaluationMetrics

        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:
        The classificationEvaluationMetrics.

      • getClassificationEvaluationMetricsOrBuilder

        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;

      • hasRegressionEvaluationMetrics

        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:
        Whether the regressionEvaluationMetrics field is set.

      • getRegressionEvaluationMetrics

        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:
        The regressionEvaluationMetrics.

      • getRegressionEvaluationMetricsOrBuilder

        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;

      • hasTranslationEvaluationMetrics

        boolean hasTranslationEvaluationMetrics()
         Model evaluation metrics for translation.
        .google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;
        Returns:
        Whether the translationEvaluationMetrics field is set.

      • getTranslationEvaluationMetrics

        TranslationEvaluationMetrics getTranslationEvaluationMetrics()
         Model evaluation metrics for translation.
        .google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;
        Returns:
        The translationEvaluationMetrics.

      • getTranslationEvaluationMetricsOrBuilder

        TranslationEvaluationMetricsOrBuilder getTranslationEvaluationMetricsOrBuilder()
         Model evaluation metrics for translation.
        .google.cloud.automl.v1beta1.TranslationEvaluationMetrics translation_evaluation_metrics = 9;

      • hasImageObjectDetectionEvaluationMetrics

        boolean hasImageObjectDetectionEvaluationMetrics()
         Model evaluation metrics for image object detection.
        .google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;
        Returns:
        Whether the imageObjectDetectionEvaluationMetrics field is set.

      • getImageObjectDetectionEvaluationMetrics

        ImageObjectDetectionEvaluationMetrics getImageObjectDetectionEvaluationMetrics()
         Model evaluation metrics for image object detection.
        .google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;
        Returns:
        The imageObjectDetectionEvaluationMetrics.

      • getImageObjectDetectionEvaluationMetricsOrBuilder

        ImageObjectDetectionEvaluationMetricsOrBuilder getImageObjectDetectionEvaluationMetricsOrBuilder()
         Model evaluation metrics for image object detection.
        .google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;

      • hasVideoObjectTrackingEvaluationMetrics

        boolean hasVideoObjectTrackingEvaluationMetrics()
         Model evaluation metrics for video object tracking.
        .google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;
        Returns:
        Whether the videoObjectTrackingEvaluationMetrics field is set.

      • getVideoObjectTrackingEvaluationMetrics

        VideoObjectTrackingEvaluationMetrics getVideoObjectTrackingEvaluationMetrics()
         Model evaluation metrics for video object tracking.
        .google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;
        Returns:
        The videoObjectTrackingEvaluationMetrics.

      • getVideoObjectTrackingEvaluationMetricsOrBuilder

        VideoObjectTrackingEvaluationMetricsOrBuilder getVideoObjectTrackingEvaluationMetricsOrBuilder()
         Model evaluation metrics for video object tracking.
        .google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics video_object_tracking_evaluation_metrics = 14;

      • hasTextSentimentEvaluationMetrics

        boolean hasTextSentimentEvaluationMetrics()
         Evaluation metrics for text sentiment models.
        .google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;
        Returns:
        Whether the textSentimentEvaluationMetrics field is set.

      • getTextSentimentEvaluationMetrics

        TextSentimentProto.TextSentimentEvaluationMetrics getTextSentimentEvaluationMetrics()
         Evaluation metrics for text sentiment models.
        .google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;
        Returns:
        The textSentimentEvaluationMetrics.

      • getTextSentimentEvaluationMetricsOrBuilder

        TextSentimentProto.TextSentimentEvaluationMetricsOrBuilder getTextSentimentEvaluationMetricsOrBuilder()
         Evaluation metrics for text sentiment models.
        .google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;

      • hasTextExtractionEvaluationMetrics

        boolean hasTextExtractionEvaluationMetrics()
         Evaluation metrics for text extraction models.
        .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;
        Returns:
        Whether the textExtractionEvaluationMetrics field is set.

      • getTextExtractionEvaluationMetrics

        TextExtractionEvaluationMetrics getTextExtractionEvaluationMetrics()
         Evaluation metrics for text extraction models.
        .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;
        Returns:
        The textExtractionEvaluationMetrics.

      • getTextExtractionEvaluationMetricsOrBuilder

        TextExtractionEvaluationMetricsOrBuilder getTextExtractionEvaluationMetricsOrBuilder()
         Evaluation metrics for text extraction models.
        .google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;

      • getName

        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:
        The name.

      • getNameBytes

        com.google.protobuf.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:
        The bytes for name.

      • getAnnotationSpecId

        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][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]
 the
 [display_name][google.cloud.automl.v1beta1.ModelEvaluation.display_name]
 field is used.
        string annotation_spec_id = 2;
        Returns:
        The annotationSpecId.

      • getAnnotationSpecIdBytes

        com.google.protobuf.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][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]
 the
 [display_name][google.cloud.automl.v1beta1.ModelEvaluation.display_name]
 field is used.
        string annotation_spec_id = 2;
        Returns:
        The bytes for annotationSpecId.

      • getDisplayName

        String getDisplayName()
         Output only. The value of
 [display_name][google.cloud.automl.v1beta1.AnnotationSpec.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.v1beta1.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.
        string display_name = 15;
        Returns:
        The displayName.

      • getDisplayNameBytes

        com.google.protobuf.ByteString getDisplayNameBytes()
         Output only. The value of
 [display_name][google.cloud.automl.v1beta1.AnnotationSpec.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.v1beta1.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.
        string display_name = 15;
        Returns:
        The bytes for displayName.

      • hasCreateTime

        boolean hasCreateTime()
         Output only. Timestamp when this model evaluation was created.
        .google.protobuf.Timestamp create_time = 5;
        Returns:
        Whether the createTime field is set.

      • getCreateTime

        com.google.protobuf.Timestamp getCreateTime()
         Output only. Timestamp when this model evaluation was created.
        .google.protobuf.Timestamp create_time = 5;
        Returns:
        The createTime.

      • getCreateTimeOrBuilder

        com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
         Output only. Timestamp when this model evaluation was created.
        .google.protobuf.Timestamp create_time = 5;

      • getEvaluatedExampleCount

        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][google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id].
        int32 evaluated_example_count = 6;
        Returns:
        The evaluatedExampleCount.