Class FeatureStatsAndAnomaly.Builder (3.55.0)

public static final class FeatureStatsAndAnomaly.Builder extends GeneratedMessageV3.Builder<FeatureStatsAndAnomaly.Builder> implements FeatureStatsAndAnomalyOrBuilder

Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.

Protobuf type google.cloud.aiplatform.v1beta1.FeatureStatsAndAnomaly

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public FeatureStatsAndAnomaly.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

build()

public FeatureStatsAndAnomaly build()
Returns
Type Description
FeatureStatsAndAnomaly

buildPartial()

public FeatureStatsAndAnomaly buildPartial()
Returns
Type Description
FeatureStatsAndAnomaly

clear()

public FeatureStatsAndAnomaly.Builder clear()
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

clearDistributionDeviation()

public FeatureStatsAndAnomaly.Builder clearDistributionDeviation()

Deviation from the current stats to baseline stats.

  1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
  2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearDriftDetected()

public FeatureStatsAndAnomaly.Builder clearDriftDetected()

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearDriftDetectionThreshold()

public FeatureStatsAndAnomaly.Builder clearDriftDetectionThreshold()

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearFeatureId()

public FeatureStatsAndAnomaly.Builder clearFeatureId()

Feature Id.

string feature_id = 1;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearFeatureMonitorId()

public FeatureStatsAndAnomaly.Builder clearFeatureMonitorId()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearFeatureMonitorJobId()

public FeatureStatsAndAnomaly.Builder clearFeatureMonitorJobId()

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

clearFeatureStats()

public FeatureStatsAndAnomaly.Builder clearFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

clearField(Descriptors.FieldDescriptor field)

public FeatureStatsAndAnomaly.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public FeatureStatsAndAnomaly.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

clearStatsTime()

public FeatureStatsAndAnomaly.Builder clearStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type Description
FeatureStatsAndAnomaly.Builder

clone()

public FeatureStatsAndAnomaly.Builder clone()
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

getDefaultInstanceForType()

public FeatureStatsAndAnomaly getDefaultInstanceForType()
Returns
Type Description
FeatureStatsAndAnomaly

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
Descriptor
Overrides

getDistributionDeviation()

public double getDistributionDeviation()

Deviation from the current stats to baseline stats.

  1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
  2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Returns
Type Description
double

The distributionDeviation.

getDriftDetected()

public boolean getDriftDetected()

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Returns
Type Description
boolean

The driftDetected.

getDriftDetectionThreshold()

public double getDriftDetectionThreshold()

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Returns
Type Description
double

The driftDetectionThreshold.

getFeatureId()

public String getFeatureId()

Feature Id.

string feature_id = 1;

Returns
Type Description
String

The featureId.

getFeatureIdBytes()

public ByteString getFeatureIdBytes()

Feature Id.

string feature_id = 1;

Returns
Type Description
ByteString

The bytes for featureId.

getFeatureMonitorId()

public String getFeatureMonitorId()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type Description
String

The featureMonitorId.

getFeatureMonitorIdBytes()

public ByteString getFeatureMonitorIdBytes()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type Description
ByteString

The bytes for featureMonitorId.

getFeatureMonitorJobId()

public long getFeatureMonitorJobId()

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Returns
Type Description
long

The featureMonitorJobId.

getFeatureStats()

public Value getFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type Description
Value

The featureStats.

getFeatureStatsBuilder()

public Value.Builder getFeatureStatsBuilder()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type Description
Builder

getFeatureStatsOrBuilder()

public ValueOrBuilder getFeatureStatsOrBuilder()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type Description
ValueOrBuilder

getStatsTime()

public Timestamp getStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type Description
Timestamp

The statsTime.

getStatsTimeBuilder()

public Timestamp.Builder getStatsTimeBuilder()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type Description
Builder

getStatsTimeOrBuilder()

public TimestampOrBuilder getStatsTimeOrBuilder()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type Description
TimestampOrBuilder

hasFeatureStats()

public boolean hasFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type Description
boolean

Whether the featureStats field is set.

hasStatsTime()

public boolean hasStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type Description
boolean

Whether the statsTime field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeFeatureStats(Value value)

public FeatureStatsAndAnomaly.Builder mergeFeatureStats(Value value)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name Description
value Value
Returns
Type Description
FeatureStatsAndAnomaly.Builder

mergeFrom(FeatureStatsAndAnomaly other)

public FeatureStatsAndAnomaly.Builder mergeFrom(FeatureStatsAndAnomaly other)
Parameter
Name Description
other FeatureStatsAndAnomaly
Returns
Type Description
FeatureStatsAndAnomaly.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public FeatureStatsAndAnomaly.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public FeatureStatsAndAnomaly.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

mergeStatsTime(Timestamp value)

public FeatureStatsAndAnomaly.Builder mergeStatsTime(Timestamp value)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name Description
value Timestamp
Returns
Type Description
FeatureStatsAndAnomaly.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final FeatureStatsAndAnomaly.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

setDistributionDeviation(double value)

public FeatureStatsAndAnomaly.Builder setDistributionDeviation(double value)

Deviation from the current stats to baseline stats.

  1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
  2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Parameter
Name Description
value double

The distributionDeviation to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setDriftDetected(boolean value)

public FeatureStatsAndAnomaly.Builder setDriftDetected(boolean value)

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Parameter
Name Description
value boolean

The driftDetected to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setDriftDetectionThreshold(double value)

public FeatureStatsAndAnomaly.Builder setDriftDetectionThreshold(double value)

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Parameter
Name Description
value double

The driftDetectionThreshold to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureId(String value)

public FeatureStatsAndAnomaly.Builder setFeatureId(String value)

Feature Id.

string feature_id = 1;

Parameter
Name Description
value String

The featureId to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureIdBytes(ByteString value)

public FeatureStatsAndAnomaly.Builder setFeatureIdBytes(ByteString value)

Feature Id.

string feature_id = 1;

Parameter
Name Description
value ByteString

The bytes for featureId to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureMonitorId(String value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorId(String value)

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Parameter
Name Description
value String

The featureMonitorId to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureMonitorIdBytes(ByteString value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorIdBytes(ByteString value)

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Parameter
Name Description
value ByteString

The bytes for featureMonitorId to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureMonitorJobId(long value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorJobId(long value)

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Parameter
Name Description
value long

The featureMonitorJobId to set.

Returns
Type Description
FeatureStatsAndAnomaly.Builder

This builder for chaining.

setFeatureStats(Value value)

public FeatureStatsAndAnomaly.Builder setFeatureStats(Value value)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name Description
value Value
Returns
Type Description
FeatureStatsAndAnomaly.Builder

setFeatureStats(Value.Builder builderForValue)

public FeatureStatsAndAnomaly.Builder setFeatureStats(Value.Builder builderForValue)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name Description
builderForValue Builder
Returns
Type Description
FeatureStatsAndAnomaly.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public FeatureStatsAndAnomaly.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public FeatureStatsAndAnomaly.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Name Description
field FieldDescriptor
index int
value Object
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides

setStatsTime(Timestamp value)

public FeatureStatsAndAnomaly.Builder setStatsTime(Timestamp value)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name Description
value Timestamp
Returns
Type Description
FeatureStatsAndAnomaly.Builder

setStatsTime(Timestamp.Builder builderForValue)

public FeatureStatsAndAnomaly.Builder setStatsTime(Timestamp.Builder builderForValue)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name Description
builderForValue Builder
Returns
Type Description
FeatureStatsAndAnomaly.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final FeatureStatsAndAnomaly.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
FeatureStatsAndAnomaly.Builder
Overrides