Out of the Box Metrics

ModelOp Center ships with multiple out-of-the-box monitors, which are registered as associated models. The user may add one of these associated monitors to his/her model or decide to write a custom metric function (see next section). These monitors can also be customized via the ModelOp monitoring Python package. See /wiki/spaces/dv33/pages/1978445995 here for documentation on the monitoring package. Here is a sampling of out of the box tests and monitors:

Quality Performance:

Ensure that model decisions and outcomes are within established data quality controls, eliminating the risk of unexpected and inaccurate decisions. Quality performance monitors include:

• Data drift of input data

• Concept drift of output

• Statistical effectiveness of model output

Risk Performance

Controlling risk and ensuring models are constantly operating within established business risk and compliance ranges as well as delivering ethically fair results is a constant challenge. Prevent out-of-compliance issues with automated, continuous risk performance monitoring. Risk performance monitors include:

• Ethical fairness of model output

• Interpretability of model features weighting

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For more details, please visit the ModelOp Center Monitoring Package section (subscribed Customers only).

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