ModelMonitoringObjectiveConfig

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

JSON representation 
{
  "trainingDataset": {
    object (TrainingDataset)
  },
  "trainingPredictionSkewDetectionConfig": {
    object (TrainingPredictionSkewDetectionConfig)
  },
  "predictionDriftDetectionConfig": {
    object (PredictionDriftDetectionConfig)
  },
  "explanationConfig": {
    object (ExplanationConfig)
  }
}
Fields
trainingDataset

object (TrainingDataset)

Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.
trainingPredictionSkewDetectionConfig

object (TrainingPredictionSkewDetectionConfig)

The config for skew between training data and prediction data.
predictionDriftDetectionConfig

object (PredictionDriftDetectionConfig)

The config for drift of prediction data.
explanationConfig

object (ExplanationConfig)

The config for integrating with Vertex Explainable AI.

TrainingDataset

Training Dataset information.

JSON representation 
{
  "dataFormat": string,
  "targetField": string,
  "loggingSamplingStrategy": {
    object (SamplingStrategy)
  },

  // Union field data_source can be only one of the following:
  "dataset": string,
  "gcsSource": {
    object (GcsSource)
  },
  "bigquerySource": {
    object (BigQuerySource)
  }
  // End of list of possible types for union field data_source.
}
Fields
dataFormat

string

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are:

"tf-record" The source file is a TFRecord file.

"csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
targetField

string

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
loggingSamplingStrategy

object (SamplingStrategy)

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

Union field data_source.

data_source can be only one of the following:
dataset

string

The resource name of the Dataset used to train this Model.
gcsSource

object (GcsSource)

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
bigquerySource

object (BigQuerySource)

The BigQuery table of the unmanaged Dataset used to train this Model.

TrainingPredictionSkewDetectionConfig

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

JSON representation 
{
  "skewThresholds": {
    string: {
      object (ThresholdConfig)
    },
    ...
  },
  "attributionScoreSkewThresholds": {
    string: {
      object (ThresholdConfig)
    },
    ...
  },
  "defaultSkewThreshold": {
    object (ThresholdConfig)
  }
}
Fields
skewThresholds

map (key: string, value: object (ThresholdConfig))

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.
attributionScoreSkewThresholds

map (key: string, value: object (ThresholdConfig))

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
defaultSkewThreshold

object (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.

PredictionDriftDetectionConfig

The config for Prediction data drift detection.

JSON representation 
{
  "driftThresholds": {
    string: {
      object (ThresholdConfig)
    },
    ...
  },
  "attributionScoreDriftThresholds": {
    string: {
      object (ThresholdConfig)
    },
    ...
  },
  "defaultDriftThreshold": {
    object (ThresholdConfig)
  }
}
Fields
driftThresholds

map (key: string, value: object (ThresholdConfig))

Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
attributionScoreDriftThresholds

map (key: string, value: object (ThresholdConfig))

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
defaultDriftThreshold

object (ThresholdConfig)

Drift 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.

ExplanationConfig

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanationSpec populated.

JSON representation 
{
  "enableFeatureAttributes": boolean,
  "explanationBaseline": {
    object (ExplanationBaseline)
  }
}
Fields
enableFeatureAttributes

boolean

If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.
explanationBaseline

object (ExplanationBaseline)

Predictions generated by the BatchPredictionJob using baseline dataset.

ExplanationBaseline

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

JSON representation 
{
  "predictionFormat": enum (PredictionFormat),

  // Union field destination can be only one of the following:
  "gcs": {
    object (GcsDestination)
  },
  "bigquery": {
    object (BigQueryDestination)
  }
  // End of list of possible types for union field destination.
}
Fields
predictionFormat

enum (PredictionFormat)

The storage format of the predictions generated BatchPrediction job.
Union field destination. The configuration specifying of BatchExplain job output. This can be used to generate the baseline of feature attribution scores. destination can be only one of the following:
gcs

object (GcsDestination)

Cloud Storage location for BatchExplain output.
bigquery

object (BigQueryDestination)

BigQuery location for BatchExplain output.

PredictionFormat

The storage format of the predictions generated BatchPrediction job.

Enums
PREDICTION_FORMAT_UNSPECIFIED Should not be set.
JSONL Predictions are in JSONL files.
BIGQUERY Predictions are in BigQuery.