Interface FeatureStatsAndAnomalyOrBuilder (3.56.0)

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public interface FeatureStatsAndAnomalyOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getDistributionDeviation()

public abstract 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 abstract 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 abstract 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 abstract String getFeatureId()

Feature Id.

string feature_id = 1;

Returns
Type	Description
String	The featureId.

getFeatureIdBytes()

public abstract ByteString getFeatureIdBytes()

Feature Id.

string feature_id = 1;

Returns
Type	Description
ByteString	The bytes for featureId.

getFeatureMonitorId()

public abstract 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 abstract 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 abstract 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 abstract 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.

getFeatureStatsOrBuilder()

public abstract 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 abstract 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.

getStatsTimeOrBuilder()

public abstract 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 abstract 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 abstract 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.