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 uses 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".
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-06-27 UTC."],[],[],null,["# FeatureStatsAndAnomaly\n\nStats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.\nFields `featureId` `string` \nfeature id.\n`featureStats` `value (`[Value](https://protobuf.dev/reference/protobuf/google.protobuf/#value)` format)` \nfeature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.\n`distributionDeviation` `number` \nDeviation 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.\n`driftDetectionThreshold` `number` \nThis is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold\n`driftDetected` `boolean` \nIf set to true, indicates current stats is detected as and comparing with baseline stats.\n`statsTime` `string (`[Timestamp](https://protobuf.dev/reference/protobuf/google.protobuf/#timestamp)` format)` \nThe timestamp we take snapshot for feature values to generate stats.\n\nUses RFC 3339, where generated output will always be Z-normalized and uses 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\"`.\n`featureMonitorJobId` `string (`[int64](https://developers.google.com/discovery/v1/type-format)` format)` \nThe id of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.\n`featureMonitorId` `string` \nThe id of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to."]]
