com.google.cloud.aiplatform.v1beta1

Interface FeatureStatsAnomalyOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

FeatureStatsAnomaly, FeatureStatsAnomaly.Builder

public interface FeatureStatsAnomalyOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
double	getAnomalyDetectionThreshold() This is the threshold used when detecting anomalies.
String	getAnomalyUri() Path of the anomaly file for current feature values in Cloud Storage bucket.
com.google.protobuf.ByteString	getAnomalyUriBytes() Path of the anomaly file for current feature values in Cloud Storage bucket.
double	getDistributionDeviation() Deviation from the current stats to baseline stats.
com.google.protobuf.Timestamp	getEndTime() The end timestamp of window where stats were generated.
com.google.protobuf.TimestampOrBuilder	getEndTimeOrBuilder() The end timestamp of window where stats were generated.
double	getScore() Feature importance score, only populated when cross-feature monitoring is enabled.
com.google.protobuf.Timestamp	getStartTime() The start timestamp of window where stats were generated.
com.google.protobuf.TimestampOrBuilder	getStartTimeOrBuilder() The start timestamp of window where stats were generated.
String	getStatsUri() Path of the stats file for current feature values in Cloud Storage bucket.
com.google.protobuf.ByteString	getStatsUriBytes() Path of the stats file for current feature values in Cloud Storage bucket.
boolean	hasEndTime() The end timestamp of window where stats were generated.
boolean	hasStartTime() The start timestamp of window where stats were generated.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getScore

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][google.cloud.aiplatform.v1beta1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW] and
 [ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT][google.cloud.aiplatform.v1beta1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT].
 

double score = 1;

Returns:

The score.

getStatsUri

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](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).
 

string stats_uri = 3;

Returns:

The statsUri.

getStatsUriBytes

com.google.protobuf.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](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).
 

string stats_uri = 3;

Returns:

The bytes for statsUri.

getAnomalyUri

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]
 (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
 

string anomaly_uri = 4;

Returns:

The anomalyUri.

getAnomalyUriBytes

com.google.protobuf.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]
 (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
 

string anomaly_uri = 4;

Returns:

The bytes for anomalyUri.

getDistributionDeviation

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 = 5;

Returns:

The distributionDeviation.

getAnomalyDetectionThreshold

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][google.cloud.aiplatform.v1beta1.ThresholdConfig.value].
 

double anomaly_detection_threshold = 9;

Returns:

The anomalyDetectionThreshold.

hasStartTime

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:

Whether the startTime field is set.

getStartTime

com.google.protobuf.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:

The startTime.

getStartTimeOrBuilder

com.google.protobuf.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;

hasEndTime

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:

Whether the endTime field is set.

getEndTime

com.google.protobuf.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:

The endTime.

getEndTimeOrBuilder

com.google.protobuf.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;