Model Audit
Audit pre and post model predictions and performance metrics to support model observability, explainability and drift management
Overview
This optional configuration provide the ability to audit predications to enable model retraining, feature and prediction drift management, model observability, and any local business governance requirements.
The configuration will dynamically create an in-memory database table, using the process name as the target table, and rest endpoints to enable direct access and export functions.
Use this feature to support external drift monitoring and model retraining
Example
Attributes
Attribute | Description | Data Type | Required |
---|---|---|---|
target schema | name of the target schema where the table will be created | String | |
queue capacity | Number of prediction results to queue before flushing to target table | Integer Default: 1000 | |
flush frequency | Frequency the queue will be flushed to table as seconds | Long Default: 60 Seconds |
Support
Contact Fractalworks for details
Last updated