abacusai.model_monitor_version

Classes

ModelMonitorVersion

A version of a model monitor

Module Contents

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, monitorDriftConfig=None, predictionDataUseMappings=None, trainingDataUseMappings=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
monitorDriftConfig (dict) – The monitor drift config for the monitor version
predictionDataUseMappings (dict) – The mapping of prediction data use to feature group version
trainingDataUseMappings (dict) – The mapping of training data use to feature group version

model_monitor_version

status

model_monitor_id

monitoring_started_at

monitoring_completed_at

training_feature_group_version

prediction_feature_group_version

error

pending_deployment_ids

failed_deployment_ids

metric_configs

feature_group_monitor_configs

metric_types

model_version

batch_prediction_version

eda_configs

training_forecast_config

prediction_forecast_config

forecast_frequency

monitor_drift_config

prediction_data_use_mappings

training_data_use_mappings

deprecated_keys

__repr__()

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

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:: DriftDistributions

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: ModelMonitorVersion

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:: ModelMonitorVersion

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:

metric_type (str) – The type of metric to get data for.
actual_values_to_detail (list) – The actual values to detail.

Returns:

Data associated with the metric.

Return type:

ModelMonitorVersionMetricData

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:: list[MonitorAlertVersion]

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:

feature_name (str) – Name of the feature to view the distribution of.
nested_feature_name (str) – Optionally, the name of the nested feature that the feature is in.

Returns:

An object describing the training and prediction output feature distributions.

Return type:

FeatureDistribution

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.

Parameters:

feature_name (str) – Name of the feature to view the distribution of.
nested_feature_name (str) – Optionally, the name of the nested feature that the feature is in.

wait_for_monitor(timeout=1200)

A waiting call until model monitor version is ready.

Parameters:: timeout (int) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.

get_status()

Gets the status of the model monitor version.

Returns:: A string describing the status of the model monitor version, for e.g., pending, complete, etc.
Return type:: str