FeatureStatsAnomaly class final
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
- ProtoMessage
- FeatureStatsAnomaly
Constructors
- FeatureStatsAnomaly({double score = 0, String statsUri = '', String anomalyUri = '', double distributionDeviation = 0, double anomalyDetectionThreshold = 0, Timestamp? startTime, Timestamp? endTime})
- FeatureStatsAnomaly.fromJson(Object? j)
-
factory
Properties
- anomalyDetectionThreshold → double
-
This is the threshold used when detecting anomalies.
The threshold can be changed by user, so this one might be different from
ThresholdConfig.value.final - anomalyUri → String
-
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).final - distributionDeviation → double
-
Deviation from the current stats to baseline stats.
final
- endTime → Timestamp?
-
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).
final
- hashCode → int
-
The hash code for this object.
no setterinherited
- qualifiedName → String
-
The fully qualified name of this message, i.e.,
google.protobuf.Durationorgoogle.rpc.ErrorInfo.finalinherited - runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
- score → double
-
Feature importance score, only populated when cross-feature monitoring is
enabled. For now only used to represent feature attribution score within
range
0, 1forModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEWandModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.final - startTime → Timestamp?
-
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).
final
- statsUri → String
-
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.
final
Methods
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
toJson(
) → Object -
override
-
toString(
) → String -
A string representation of this object.
override
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited
Constants
- fullyQualifiedName → const String