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public interface FeatureStatsAnomalyOrBuilder extends MessageOrBuilderImplements
MessageOrBuilderMethods
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;
| 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;
| 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;
| Type | Description |
| ByteString | The bytes for anomalyUri. |
getDistributionDeviation()
public abstract 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 = 5;
| 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;
| 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;
| 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;
| 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;
| 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;
| 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;
| 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;
| 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;
| 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;
| Type | Description |
| boolean | Whether the startTime field is set. |