Package com.google.cloud.automl.v1

Class ClassificationEvaluationMetrics.Builder

    • Method Detail

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.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.GeneratedMessageV3.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

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.Builder>

      • 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.

      • 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.

      • 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.

      • 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;

      • 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;

      • 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.

      • 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.