abacusai.model_monitor_version
Module Contents
Classes
A version of a model monitor |
- class abacusai.model_monitor_version.ModelMonitorVersion(client, modelMonitorVersion=None, status=None, modelMonitorId=None, monitoringStartedAt=None, monitoringCompletedAt=None, trainingFeatureGroupVersion=None, predictionFeatureGroupVersion=None, error=None, pendingDeploymentIds=None, failedDeploymentIds=None, metricConfigs=None, featureGroupMonitorConfigs=None, metricTypes=None, modelVersion=None, batchPredictionVersion=None, edaConfigs=None, trainingForecastConfig=None, predictionForecastConfig=None, forecastFrequency=None)
Bases:
abacusai.return_class.AbstractApiClass
A version of a model monitor
- Parameters:
client (ApiClient) – An authenticated API Client instance
modelMonitorVersion (str) – The unique identifier of a model monitor version.
status (str) – The current status of the model.
modelMonitorId (str) – A reference to the model monitor this version belongs to.
monitoringStartedAt (str) – The start time and date of the monitoring process.
monitoringCompletedAt (str) – The end time and date of the monitoring process.
trainingFeatureGroupVersion (list[str]) – Feature group version IDs that this refresh pipeline run is monitoring.
predictionFeatureGroupVersion (list[str]) – Feature group version IDs that this refresh pipeline run is monitoring.
error (str) – Relevant error if the status is FAILED.
pendingDeploymentIds (list) – List of deployment IDs where deployment is pending.
failedDeploymentIds (list) – List of failed deployment IDs.
metricConfigs (list[dict]) – List of metric configs for the model monitor instance.
featureGroupMonitorConfigs (dict) – Configurations for feature group monitor
metricTypes (list) – List of metric types.
modelVersion (list[str]) – Model version IDs that this refresh pipeline run is monitoring.
batchPredictionVersion (str) – The batch prediction version this model monitor is monitoring
edaConfigs (list) – The list of eda configs for the version
trainingForecastConfig (dict) – The training forecast config for the monitor version
predictionForecastConfig (dict) – The prediction forecast config for the monitor version
forecastFrequency (str) – The forecast frequency for the monitor version
- __repr__()
Return repr(self).
- to_dict()
Get a dict representation of the parameters in this class
- Returns:
The dict value representation of the class parameters
- Return type:
- get_prediction_drift()
Gets the label and prediction drifts for a model monitor.
- Parameters:
model_monitor_version (str) – Unique string identifier for a model monitor version created under the project.
- Returns:
Object describing training and prediction output label and prediction distributions.
- Return type:
- refresh()
Calls describe and refreshes the current object’s fields
- Returns:
The current object
- Return type:
- describe()
Retrieves a full description of the specified model monitor version.
- Parameters:
model_monitor_version (str) – The unique version ID of the model monitor version.
- Returns:
A model monitor version.
- Return type:
- delete()
Deletes the specified model monitor version.
- Parameters:
model_monitor_version (str) – Unique identifier of the model monitor version to delete.
- metric_data(metric_type, actual_values_to_detail=None)
Provides the data needed for decile metrics associated with the model monitor.
- Parameters:
- Returns:
Data associated with the metric.
- Return type:
- list_monitor_alert_versions_for_monitor_version()
Retrieves the list of monitor alert versions for a specified monitor instance.
- Parameters:
model_monitor_version (str) – The unique ID associated with the model monitor.
- Returns:
A list of monitor alert versions.
- Return type:
- get_model_monitoring_logs(stdout=False, stderr=False)
Returns monitoring logs for the model.
- Parameters:
- Returns:
A function logs.
- Return type:
- get_drift_for_feature(feature_name, nested_feature_name=None)
Gets the feature drift associated with a single feature in an output feature group from a prediction.
- Parameters:
- Returns:
An object describing the training and prediction output feature distributions.
- Return type:
- get_outliers_for_feature(feature_name=None, nested_feature_name=None)
Gets a list of outliers measured by a single feature (or overall) in an output feature group from a prediction.