public static final class ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder extends GeneratedMessageV3.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder> implements ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder
Summary statistics for a population of values.
Protobuf type
google.cloud.aiplatform.v1beta1.ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue
Inherited Members
com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)
com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)
com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)
Static Methods
public static final Descriptors.Descriptor getDescriptor()
Methods
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue build()
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue buildPartial()
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clear()
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistribution()
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistributionDeviation()
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;
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearField(Descriptors.FieldDescriptor field)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clone()
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue getDefaultInstanceForType()
public Descriptors.Descriptor getDescriptorForType()
Overrides
public Value getDistribution()
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
Returns |
Type |
Description |
Value |
The distribution.
|
public Value.Builder getDistributionBuilder()
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
public 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 |
Type |
Description |
double |
The distributionDeviation.
|
public ValueOrBuilder getDistributionOrBuilder()
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
public boolean hasDistribution()
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
Returns |
Type |
Description |
boolean |
Whether the distribution field is set.
|
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeDistribution(Value value)
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
Parameter |
Name |
Description |
value |
Value
|
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue other)
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(Message other)
Parameter |
Name |
Description |
other |
Message
|
Overrides
public final ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(Value value)
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
Parameter |
Name |
Description |
value |
Value
|
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(Value.Builder builderForValue)
tensorflow.metadata.v0.DatasetFeatureStatistics format.
.google.protobuf.Value distribution = 1;
Parameter |
Name |
Description |
builderForValue |
Builder
|
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistributionDeviation(double value)
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;
Parameter |
Name |
Description |
value |
double
The distributionDeviation to set.
|
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setField(Descriptors.FieldDescriptor field, Object value)
Overrides
public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Overrides
public final ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setUnknownFields(UnknownFieldSet unknownFields)
Overrides