Interface FeatureStatsAnomalyOrBuilder (3.5.0)

Version 3.5.0

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public interface FeatureStatsAnomalyOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getAnomalyDetectionThreshold()

public abstract double getAnomalyDetectionThreshold()

This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.

double anomaly_detection_threshold = 9;

Returns

Type	Description
double	The anomalyDetectionThreshold.

getAnomalyUri()

public abstract String getAnomalyUri()

Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs://<bucket_name>/<object_name>/anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message tensorflow.metadata.v0.AnomalyInfo.

string anomaly_uri = 4;

Returns

Type	Description
String	The anomalyUri.

getAnomalyUriBytes()

public abstract ByteString getAnomalyUriBytes()

Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs://<bucket_name>/<object_name>/anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message tensorflow.metadata.v0.AnomalyInfo.

string anomaly_uri = 4;

Returns

Type	Description
ByteString	The bytes for anomalyUri.

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\u2013Shannon divergence.

double distribution_deviation = 5;

Returns

Type	Description
double	The distributionDeviation.

getEndTime()

public abstract Timestamp getEndTime()

The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).

.google.protobuf.Timestamp end_time = 8;

Returns

Type	Description
Timestamp	The endTime.

getEndTimeOrBuilder()

public abstract TimestampOrBuilder getEndTimeOrBuilder()

The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).

.google.protobuf.Timestamp end_time = 8;

Returns

Type	Description
TimestampOrBuilder

getScore()

public abstract double getScore()

Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.

double score = 1;

Returns

Type	Description
double	The score.

getStartTime()

public abstract Timestamp getStartTime()

The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).

.google.protobuf.Timestamp start_time = 7;

Returns

Type	Description
Timestamp	The startTime.

getStartTimeOrBuilder()

public abstract TimestampOrBuilder getStartTimeOrBuilder()

The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).

.google.protobuf.Timestamp start_time = 7;

Returns

Type	Description
TimestampOrBuilder

getStatsUri()

public abstract String getStatsUri()

Path of the stats file for current feature values in Cloud Storage bucket. Format: gs://<bucket_name>/<object_name>/stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.

string stats_uri = 3;

Returns

Type	Description
String	The statsUri.

getStatsUriBytes()

public abstract ByteString getStatsUriBytes()

Path of the stats file for current feature values in Cloud Storage bucket. Format: gs://<bucket_name>/<object_name>/stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.

string stats_uri = 3;

Returns

Type	Description
ByteString	The bytes for statsUri.

hasEndTime()

public abstract boolean hasEndTime()

The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).

.google.protobuf.Timestamp end_time = 8;

Returns

Type	Description
boolean	Whether the endTime field is set.

hasStartTime()

public abstract boolean hasStartTime()

The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).

.google.protobuf.Timestamp start_time = 7;

Returns

Type	Description
boolean	Whether the startTime field is set.