Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
featureIdstring
feature id.
feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.
distributionDeviationnumber
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.
driftDetectionThresholdnumber
This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold
driftDetectedboolean
If set to true, indicates current stats is detected as and comparing with baseline stats.
The timestamp we take snapshot for feature values to generate stats.
Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
The id of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.
featureMonitorIdstring
The id of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.
| JSON representation |
|---|
{ "featureId": string, "featureStats": value, "distributionDeviation": number, "driftDetectionThreshold": number, "driftDetected": boolean, "statsTime": string, "featureMonitorJobId": string, "featureMonitorId": string } |