Package com.google.cloud.aiplatform.v1beta1

Interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue, ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Enclosing class:
ModelMonitoringStatsDataPoint.TypedValue
public static interface ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Summary

    Modifier and Type
    Method
    Description
    com.google.protobuf.Value
    getDistribution()
    Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
    double
    getDistributionDeviation()
    Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics
    com.google.protobuf.ValueOrBuilder
    getDistributionOrBuilder()
    Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
    boolean
    hasDistribution()
    Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.

    Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

    isInitialized

    Methods inherited from interface com.google.protobuf.MessageOrBuilder

    findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

  • Method Details

    • hasDistribution

      boolean hasDistribution()
       Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
      .google.protobuf.Value distribution = 1;
      Returns:
      Whether the distribution field is set.

    • getDistribution

      com.google.protobuf.Value getDistribution()
       Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
      .google.protobuf.Value distribution = 1;
      Returns:
      The distribution.

    • getDistributionOrBuilder

      com.google.protobuf.ValueOrBuilder getDistributionOrBuilder()
       Predictive monitoring drift distribution in
 `tensorflow.metadata.v0.DatasetFeatureStatistics` format.
      .google.protobuf.Value distribution = 1;

    • getDistributionDeviation

      double getDistributionDeviation()
       Distribution distance deviation from the current dataset's statistics
 to baseline dataset's statistics.
 * For categorical feature, the distribution distance is calculated
 by L-inifinity norm or Jensen–Shannon divergence.
 * For numerical feature, the distribution distance is calculated by
 Jensen–Shannon divergence.
      double distribution_deviation = 2;
      Returns:
      The distributionDeviation.