Method
createModelMonitor POST
Copy POST

Runs a model monitor for the specified project.

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes projectId str The unique ID associated with the project.
Yes predictionFeatureGroupId str The unique ID of the prediction data feature group.
No trainingFeatureGroupId str The unique ID of the training data feature group.
No name str The name you want your model monitor to have. Defaults to " Model Monitor".
No refreshSchedule str A cron-style string that describes a schedule in UTC to automatically retrain the created model monitor.
No targetValue str A target positive value for the label to compute bias and PR/AUC for performance page.
No targetValueBias str A target positive value for the label to compute bias.
No targetValuePerformance str A target positive value for the label to compute PR curve/AUC for performance page.
No featureMappings dict A JSON map to override features for prediction_feature_group, where keys are column names and the values are feature data use types.
No modelId str The unique ID of the model.
No trainingFeatureMappings dict A JSON map to override features for training_fature_group, where keys are column names and the values are feature data use types.
No featureGroupBaseMonitorConfig dict Selection strategy for the feature_group 1 with the feature group version if selected.
No featureGroupComparisonMonitorConfig dict Selection strategy for the feature_group 1 with the feature group version if selected.
No excludeInteractivePerformanceAnalysis bool Whether to exclude interactive performance analysis. Defaults to True if not provided.
No excludeBiasAnalysis bool Whether to exclude bias analysis in the model monitor. For default value bias analysis is included.
No excludePerformanceAnalysis bool Whether to exclude performance analysis in the model monitor. For default value performance analysis is included.
No excludeFeatureDriftAnalysis bool Whether to exclude feature drift analysis in the model monitor. For default value feature drift analysis is included.
No excludeDataIntegrityAnalysis bool Whether to exclude data integrity analysis in the model monitor. For default value data integrity analysis is included.
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY TYPE DESCRIPTION
success Boolean true if the call succeeded, false if there was an error
result ModelMonitor
KEY TYPE Description
modelMonitorId str The unique identifier of the model monitor.
name str The user-friendly name for the model monitor.
createdAt str Date and time at which the model was created.
projectId str The project this model belongs to.
trainingFeatureGroupId List[str] Feature group IDs that this model monitor is monitoring.
predictionFeatureGroupId List[str] Feature group IDs that this model monitor is monitoring.
predictionFeatureGroupVersion List[str] Feature group versions that this model monitor is monitoring.
trainingFeatureGroupVersion List[str] Feature group versions that this model monitor is monitoring.
alertConfig dict Alerting configuration for this model monitor.
biasMetricId str The bias metric ID
metricConfigs dict Configurations for model monitor
featureGroupMonitorConfigs dict Configurations for feature group monitor
metricTypes dict List of metric types
modelId str Model ID that this model monitor is monitoring.
starred bool Whether this model monitor is starred.
batchPredictionId str The batch prediction ID this model monitor monitors
monitorType str The type of the monitor, one of MODEL_MONITOR, or FEATURE_GROUP_MONITOR
edaConfigs dict The configs for EDA
trainingForecastConfig dict The tarining config for forecast monitors
predictionForecastConfig dict The prediction config for forecast monitors
forecastFrequency str The frequency of the forecast
trainingFeatureGroupSampling bool Whether or not we sample from training feature group
predictionFeatureGroupSampling bool Whether or not we sample from prediction feature group
monitorDriftConfig dict The monitor drift config for the monitor
predictionDataUseMappings dict The data_use mapping of the prediction features
trainingDataUseMappings dict The data_use mapping of the training features
latestMonitorModelVersion ModelMonitorVersion The latest model monitor version.
refreshSchedules RefreshSchedule List of refresh schedules that indicate when the next model version will be trained.

Exceptions:

TYPE WHEN
DataNotFoundError

projectId is not found.
DataNotFoundError

predictionFeatureGroupId is not found.
DataNotFoundError

trainingFeatureGroupId is not found.
DataNotFoundError

modelId is not found.
ConflictError

The project has validation errors.
InvalidParameterError

A supplied parameter is invalid.
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