Package com.google.cloud.automl.v1

Class ClassificationEvaluationMetrics.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder>
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.Builder
All Implemented Interfaces:
ClassificationEvaluationMetricsOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
ClassificationEvaluationMetrics
public static final class ClassificationEvaluationMetrics.Builder extends com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder> implements ClassificationEvaluationMetricsOrBuilder
 Model evaluation metrics for classification problems.
 Note: For Video Classification this metrics only describe quality of the
 Video Classification predictions of "segment_classification" type.
Protobuf type google.cloud.automl.v1.ClassificationEvaluationMetrics

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder>

    • clear

      public ClassificationEvaluationMetrics.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder>

    • getDefaultInstanceForType

      public ClassificationEvaluationMetrics getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public ClassificationEvaluationMetrics build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public ClassificationEvaluationMetrics buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public ClassificationEvaluationMetrics.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.Builder>

    • mergeFrom

      public ClassificationEvaluationMetrics.Builder mergeFrom(ClassificationEvaluationMetrics other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.Builder>

    • mergeFrom

      public ClassificationEvaluationMetrics.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.Builder>
      Throws:
      IOException

    • getAuPrc

      public float getAuPrc()
       Output only. The Area Under Precision-Recall Curve metric. Micro-averaged
 for the overall evaluation.
      float au_prc = 1;
      Specified by:
      getAuPrc in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      The auPrc.

    • setAuPrc

      public ClassificationEvaluationMetrics.Builder setAuPrc(float value)
       Output only. The Area Under Precision-Recall Curve metric. Micro-averaged
 for the overall evaluation.
      float au_prc = 1;
      Parameters:
      value - The auPrc to set.
      Returns:
      This builder for chaining.

    • clearAuPrc

      public ClassificationEvaluationMetrics.Builder clearAuPrc()
       Output only. The Area Under Precision-Recall Curve metric. Micro-averaged
 for the overall evaluation.
      float au_prc = 1;
      Returns:
      This builder for chaining.

    • getAuRoc

      public float getAuRoc()
       Output only. The Area Under Receiver Operating Characteristic curve metric.
 Micro-averaged for the overall evaluation.
      float au_roc = 6;
      Specified by:
      getAuRoc in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      The auRoc.

    • setAuRoc

      public ClassificationEvaluationMetrics.Builder setAuRoc(float value)
       Output only. The Area Under Receiver Operating Characteristic curve metric.
 Micro-averaged for the overall evaluation.
      float au_roc = 6;
      Parameters:
      value - The auRoc to set.
      Returns:
      This builder for chaining.

    • clearAuRoc

      public ClassificationEvaluationMetrics.Builder clearAuRoc()
       Output only. The Area Under Receiver Operating Characteristic curve metric.
 Micro-averaged for the overall evaluation.
      float au_roc = 6;
      Returns:
      This builder for chaining.

    • getLogLoss

      public float getLogLoss()
       Output only. The Log Loss metric.
      float log_loss = 7;
      Specified by:
      getLogLoss in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      The logLoss.

    • setLogLoss

      public ClassificationEvaluationMetrics.Builder setLogLoss(float value)
       Output only. The Log Loss metric.
      float log_loss = 7;
      Parameters:
      value - The logLoss to set.
      Returns:
      This builder for chaining.

    • clearLogLoss

      public ClassificationEvaluationMetrics.Builder clearLogLoss()
       Output only. The Log Loss metric.
      float log_loss = 7;
      Returns:
      This builder for chaining.

    • getConfidenceMetricsEntryList

      public List<ClassificationEvaluationMetrics.ConfidenceMetricsEntry> getConfidenceMetricsEntryList()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
      Specified by:
      getConfidenceMetricsEntryList in interface ClassificationEvaluationMetricsOrBuilder

    • getConfidenceMetricsEntryCount

      public int getConfidenceMetricsEntryCount()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
      Specified by:
      getConfidenceMetricsEntryCount in interface ClassificationEvaluationMetricsOrBuilder

    • getConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.ConfidenceMetricsEntry getConfidenceMetricsEntry(int index)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
      Specified by:
      getConfidenceMetricsEntry in interface ClassificationEvaluationMetricsOrBuilder

    • setConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder setConfidenceMetricsEntry(int index, ClassificationEvaluationMetrics.ConfidenceMetricsEntry value)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • setConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder setConfidenceMetricsEntry(int index, ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder builderForValue)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder addConfidenceMetricsEntry(ClassificationEvaluationMetrics.ConfidenceMetricsEntry value)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder addConfidenceMetricsEntry(int index, ClassificationEvaluationMetrics.ConfidenceMetricsEntry value)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder addConfidenceMetricsEntry(ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder builderForValue)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder addConfidenceMetricsEntry(int index, ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder builderForValue)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addAllConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder addAllConfidenceMetricsEntry(Iterable<? extends ClassificationEvaluationMetrics.ConfidenceMetricsEntry> values)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • clearConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder clearConfidenceMetricsEntry()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • removeConfidenceMetricsEntry

      public ClassificationEvaluationMetrics.Builder removeConfidenceMetricsEntry(int index)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • getConfidenceMetricsEntryBuilder

      public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder getConfidenceMetricsEntryBuilder(int index)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • getConfidenceMetricsEntryOrBuilder

      public ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder getConfidenceMetricsEntryOrBuilder(int index)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
      Specified by:
      getConfidenceMetricsEntryOrBuilder in interface ClassificationEvaluationMetricsOrBuilder

    • getConfidenceMetricsEntryOrBuilderList

      public List<? extends ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder> getConfidenceMetricsEntryOrBuilderList()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
      Specified by:
      getConfidenceMetricsEntryOrBuilderList in interface ClassificationEvaluationMetricsOrBuilder

    • addConfidenceMetricsEntryBuilder

      public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder addConfidenceMetricsEntryBuilder()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • addConfidenceMetricsEntryBuilder

      public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder addConfidenceMetricsEntryBuilder(int index)
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • getConfidenceMetricsEntryBuilderList

      public List<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder> getConfidenceMetricsEntryBuilderList()
       Output only. Metrics for each confidence_threshold in
 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
 position_threshold = INT32_MAX_VALUE.
 ROC and precision-recall curves, and other aggregated metrics are derived
 from them. The confidence metrics entries may also be supplied for
 additional values of position_threshold, but from these no aggregated
 metrics are computed.
      repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

    • hasConfusionMatrix

      public boolean hasConfusionMatrix()
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
      Specified by:
      hasConfusionMatrix in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      Whether the confusionMatrix field is set.

    • getConfusionMatrix

      public ClassificationEvaluationMetrics.ConfusionMatrix getConfusionMatrix()
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
      Specified by:
      getConfusionMatrix in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      The confusionMatrix.

    • setConfusionMatrix

      public ClassificationEvaluationMetrics.Builder setConfusionMatrix(ClassificationEvaluationMetrics.ConfusionMatrix value)
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

    • setConfusionMatrix

      public ClassificationEvaluationMetrics.Builder setConfusionMatrix(ClassificationEvaluationMetrics.ConfusionMatrix.Builder builderForValue)
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

    • mergeConfusionMatrix

      public ClassificationEvaluationMetrics.Builder mergeConfusionMatrix(ClassificationEvaluationMetrics.ConfusionMatrix value)
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

    • clearConfusionMatrix

      public ClassificationEvaluationMetrics.Builder clearConfusionMatrix()
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

    • getConfusionMatrixBuilder

      public ClassificationEvaluationMetrics.ConfusionMatrix.Builder getConfusionMatrixBuilder()
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

    • getConfusionMatrixOrBuilder

      public ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder getConfusionMatrixOrBuilder()
       Output only. Confusion matrix of the evaluation.
 Only set for MULTICLASS classification problems where number
 of labels is no more than 10.
 Only set for model level evaluation, not for evaluation per label.
      .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
      Specified by:
      getConfusionMatrixOrBuilder in interface ClassificationEvaluationMetricsOrBuilder

    • getAnnotationSpecIdList

      public com.google.protobuf.ProtocolStringList getAnnotationSpecIdList()
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Specified by:
      getAnnotationSpecIdList in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      A list containing the annotationSpecId.

    • getAnnotationSpecIdCount

      public int getAnnotationSpecIdCount()
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Specified by:
      getAnnotationSpecIdCount in interface ClassificationEvaluationMetricsOrBuilder
      Returns:
      The count of annotationSpecId.

    • getAnnotationSpecId

      public String getAnnotationSpecId(int index)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Specified by:
      getAnnotationSpecId in interface ClassificationEvaluationMetricsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The annotationSpecId at the given index.

    • getAnnotationSpecIdBytes

      public com.google.protobuf.ByteString getAnnotationSpecIdBytes(int index)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Specified by:
      getAnnotationSpecIdBytes in interface ClassificationEvaluationMetricsOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the annotationSpecId at the given index.

    • setAnnotationSpecId

      public ClassificationEvaluationMetrics.Builder setAnnotationSpecId(int index, String value)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Parameters:
      index - The index to set the value at.
      value - The annotationSpecId to set.
      Returns:
      This builder for chaining.

    • addAnnotationSpecId

      public ClassificationEvaluationMetrics.Builder addAnnotationSpecId(String value)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Parameters:
      value - The annotationSpecId to add.
      Returns:
      This builder for chaining.

    • addAllAnnotationSpecId

      public ClassificationEvaluationMetrics.Builder addAllAnnotationSpecId(Iterable<String> values)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Parameters:
      values - The annotationSpecId to add.
      Returns:
      This builder for chaining.

    • clearAnnotationSpecId

      public ClassificationEvaluationMetrics.Builder clearAnnotationSpecId()
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Returns:
      This builder for chaining.

    • addAnnotationSpecIdBytes

      public ClassificationEvaluationMetrics.Builder addAnnotationSpecIdBytes(com.google.protobuf.ByteString value)
       Output only. The annotation spec ids used for this evaluation.
      repeated string annotation_spec_id = 5;
      Parameters:
      value - The bytes of the annotationSpecId to add.
      Returns:
      This builder for chaining.