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public static final class FeatureStatsAndAnomaly.Builder extends GeneratedMessageV3.Builder<FeatureStatsAndAnomaly.Builder> implements FeatureStatsAndAnomalyOrBuilderStats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
Protobuf type google.cloud.aiplatform.v1beta1.FeatureStatsAndAnomaly
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > FeatureStatsAndAnomaly.BuilderImplements
FeatureStatsAndAnomalyOrBuilderStatic 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 |
|
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 |
|
clearDistributionDeviation()
public FeatureStatsAndAnomaly.Builder clearDistributionDeviation()Deviation from the current stats to baseline stats.
- For categorical feature, the distribution distance is calculated by L-inifinity norm.
- 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 |
|
clearOneof(Descriptors.OneofDescriptor oneof)
public FeatureStatsAndAnomaly.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
FeatureStatsAndAnomaly.Builder |
|
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 |
|
getDefaultInstanceForType()
public FeatureStatsAndAnomaly getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
FeatureStatsAndAnomaly |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getDistributionDeviation()
public double getDistributionDeviation()Deviation from the current stats to baseline stats.
- For categorical feature, the distribution distance is calculated by L-inifinity norm.
- 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 |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
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 |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public FeatureStatsAndAnomaly.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
FeatureStatsAndAnomaly.Builder |
|
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 |
|
setDistributionDeviation(double value)
public FeatureStatsAndAnomaly.Builder setDistributionDeviation(double value)Deviation from the current stats to baseline stats.
- For categorical feature, the distribution distance is calculated by L-inifinity norm.
- For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
double distribution_deviation = 3;
| Parameter | |
|---|---|
| Name | Description |
value |
doubleThe 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 |
booleanThe 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 |
doubleThe 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 |
StringThe 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 |
ByteStringThe 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 |
StringThe 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 |
ByteStringThe 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 |
longThe 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 |
|
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 |
|
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 |
|