Resource: Feature
Feature Metadata information that describes an attribute of an entity type. For example, apple is an entity type, and color is a feature that describes apple.
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{ "name": string, "description": string, "valueType": enum ( |
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name |
Immutable. Name of the Feature. Format: The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type. |
description |
Description of the Feature. |
valueType |
Required. Immutable. Type of Feature value. |
createTime |
Output only. Timestamp when this EntityType was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
updateTime |
Output only. Timestamp when this EntityType was most recently updated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
labels |
Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. |
etag |
Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. |
monitoringConfig |
Optional. The custom monitoring configuration for this Feature, if not set, use the monitoringConfig defined for the EntityType this Feature belongs to. Only Features with type ( If this is populated with [FeaturestoreMonitoringConfig.disabled][] = true, snapshot analysis monitoring is disabled; if [FeaturestoreMonitoringConfig.monitoring_interval][] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring config is same as the EntityType's this Feature belongs to. |
disableMonitoring |
Optional. If not set, use the monitoringConfig defined for the EntityType this Feature belongs to. Only Features with type ( If set to true, all types of data monitoring are disabled despite the config on EntityType. |
monitoringStats[] |
Output only. A list of historical [Snapshot Analysis][FeaturestoreMonitoringConfig.SnapshotAnalysis] stats requested by user, sorted by |
monitoringStatsAnomalies[] |
Output only. The list of historical stats and anomalies with specified objectives. |
ValueType
An enum representing the value type of a feature.
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VALUE_TYPE_UNSPECIFIED |
The value type is unspecified. |
BOOL |
Used for Feature that is a boolean. |
BOOL_ARRAY |
Used for Feature that is a list of boolean. |
DOUBLE |
Used for Feature that is double. |
DOUBLE_ARRAY |
Used for Feature that is a list of double. |
INT64 |
Used for Feature that is INT64. |
INT64_ARRAY |
Used for Feature that is a list of INT64. |
STRING |
Used for Feature that is string. |
STRING_ARRAY |
Used for Feature that is a list of String. |
BYTES |
Used for Feature that is bytes. |
FeatureStatsAnomaly
Stats and Anomaly generated at specific timestamp for specific Feature. The startTime and endTime 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, startTime = endTime. Timestamp of the stats and anomalies always refers to endTime. Raw stats and anomalies are stored in statsUri or anomalyUri in the tensorflow defined protos. Field dataStats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.
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{ "score": number, "statsUri": string, "anomalyUri": string, "distributionDeviation": number, "anomalyDetectionThreshold": number, "startTime": string, "endTime": string } |
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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 |
statsUri |
Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:// |
anomalyUri |
Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:// |
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. |
anomalyDetectionThreshold |
This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from |
startTime |
The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), startTime is only used to indicate the monitoring intervals, so it always equals to (endTime - monitoringInterval). A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
endTime |
The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), endTime indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values). A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
MonitoringStatsAnomaly
A list of historical [Snapshot Analysis][FeaturestoreMonitoringConfig.SnapshotAnalysis] or [Import Feature Analysis] [FeaturestoreMonitoringConfig.ImportFeatureAnalysis] stats requested by user, sorted by FeatureStatsAnomaly.start_time
descending.
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{ "objective": enum ( |
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objective |
Output only. The objective for each stats. |
featureStatsAnomaly |
Output only. The stats and anomalies generated at specific timestamp. |
Objective
If the objective in the request is both Import Feature Analysis and Snapshot Analysis, this objective could be one of them. Otherwise, this objective should be the same as the objective in the request.
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OBJECTIVE_UNSPECIFIED |
If it's OBJECTIVE_UNSPECIFIED, monitoringStats will be empty. |
IMPORT_FEATURE_ANALYSIS |
Stats are generated by Import Feature Analysis. |
SNAPSHOT_ANALYSIS |
Stats are generated by Snapshot Analysis. |
Methods |
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Creates a batch of Features in a given EntityType. |
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Creates a new Feature in a given EntityType. |
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Deletes a single Feature. |
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Gets details of a single Feature. |
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Lists Features in a given EntityType. |
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Updates the parameters of a single Feature. |