- 1.18.0 (latest)
- 1.17.0
- 1.16.0
- 1.15.0
- 1.14.0
- 1.13.1
- 1.12.0
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.0
- 1.7.0
- 1.6.0
- 1.5.0
- 1.4.0
- 1.3.0
- 1.2.0
- 1.1.0
- 1.0.0
- 0.39.0
- 0.38.0
- 0.37.1
- 0.32.0
- 0.31.0
- 0.30.0
- 0.29.0
- 0.28.0
- 0.27.0
- 0.26.2
- 0.25.0
- 0.24.0
- 0.23.0
- 0.22.0
- 0.21.0
- 0.20.0
- 0.19.0
- 0.18.0
- 0.17.0
- 0.16.0
- 0.15.0
- 0.13.0
- 0.12.0
- 0.11.1
- 0.10.0
Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class TrainingPredictionSkewDetectionConfig.
The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.
Generated from protobuf message google.cloud.aiplatform.v1.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig
Namespace
Google \ Cloud \ AIPlatform \ V1 \ ModelMonitoringObjectiveConfigMethods
__construct
Constructor.
Parameters | |
---|---|
Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ skew_thresholds |
array|Google\Protobuf\Internal\MapField
Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature. |
↳ attribution_score_skew_thresholds |
array|Google\Protobuf\Internal\MapField
Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature. |
↳ default_skew_threshold |
Google\Cloud\AIPlatform\V1\ThresholdConfig
Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features. |
getSkewThresholds
Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
Returns | |
---|---|
Type | Description |
Google\Protobuf\Internal\MapField |
setSkewThresholds
Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
Parameter | |
---|---|
Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
Returns | |
---|---|
Type | Description |
$this |
getAttributionScoreSkewThresholds
Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
Returns | |
---|---|
Type | Description |
Google\Protobuf\Internal\MapField |
setAttributionScoreSkewThresholds
Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
Parameter | |
---|---|
Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
Returns | |
---|---|
Type | Description |
$this |
getDefaultSkewThreshold
Skew anomaly detection threshold used by all features.
When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
Returns | |
---|---|
Type | Description |
Google\Cloud\AIPlatform\V1\ThresholdConfig|null |
hasDefaultSkewThreshold
clearDefaultSkewThreshold
setDefaultSkewThreshold
Skew anomaly detection threshold used by all features.
When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
Parameter | |
---|---|
Name | Description |
var |
Google\Cloud\AIPlatform\V1\ThresholdConfig
|
Returns | |
---|---|
Type | Description |
$this |