Class GoogleCloudAiplatformV1beta1FeatureStatsAnomaly

Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.

Inheritance

object

GoogleCloudAiplatformV1beta1FeatureStatsAnomaly

Implements

IDirectResponseSchema

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Google.Apis.Aiplatform.v1beta1.Data

Assembly: Google.Apis.Aiplatform.v1beta1.dll

Syntax

public class GoogleCloudAiplatformV1beta1FeatureStatsAnomaly : IDirectResponseSchema

Properties

AnomalyDetectionThreshold

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

Declaration

[JsonProperty("anomalyDetectionThreshold")]
public virtual double? AnomalyDetectionThreshold { get; set; }

Property Value

Type	Description
double?

AnomalyUri

Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////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).

Declaration

[JsonProperty("anomalyUri")]
public virtual string AnomalyUri { get; set; }

Property Value

Type	Description
string

DistributionDeviation

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.

Declaration

[JsonProperty("distributionDeviation")]
public virtual double? DistributionDeviation { get; set; }

Property Value

Type	Description
double?

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
string

EndTime

object representation of EndTimeRaw.

Declaration

[JsonIgnore]
[Obsolete("This property is obsolete and may behave unexpectedly; please use EndTimeDateTimeOffset instead.")]
public virtual object EndTime { get; set; }

Property Value

Type	Description
object

EndTimeDateTimeOffset

DateTimeOffset representation of EndTimeRaw.

Declaration

[JsonIgnore]
public virtual DateTimeOffset? EndTimeDateTimeOffset { get; set; }

Property Value

Type	Description
DateTimeOffset?

EndTimeRaw

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).

Declaration

[JsonProperty("endTime")]
public virtual string EndTimeRaw { get; set; }

Property Value

Type	Description
string

Score

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.

Declaration

[JsonProperty("score")]
public virtual double? Score { get; set; }

Property Value

Type	Description
double?

StartTime

object representation of StartTimeRaw.

Declaration

[JsonIgnore]
[Obsolete("This property is obsolete and may behave unexpectedly; please use StartTimeDateTimeOffset instead.")]
public virtual object StartTime { get; set; }

Property Value

Type	Description
object

StartTimeDateTimeOffset

DateTimeOffset representation of StartTimeRaw.

Declaration

[JsonIgnore]
public virtual DateTimeOffset? StartTimeDateTimeOffset { get; set; }

Property Value

Type	Description
DateTimeOffset?

StartTimeRaw

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).

Declaration

[JsonProperty("startTime")]
public virtual string StartTimeRaw { get; set; }

Property Value

Type	Description
string

StatsUri

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

Declaration

[JsonProperty("statsUri")]
public virtual string StatsUri { get; set; }

Property Value

Type	Description
string

Implements

IDirectResponseSchema