Champion/Challenger Model Comparison

This section describes the Champion/Challenger feature in ModelOp Center, and how to use it to help determine the best model method or approach to promote to production.


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Data Science requires experimentation using a variety of methods, approaches, frameworks, and potentially even coding languages. While most data scientists will conduct their experimentation in their model development environment, data scientists--and the managerial and governance reviewers--often want to review that a candidate model for production performs better than any currently running version of the model. The Champion/Challenger feature in ModelOp Center presents a side-by side comparison of the performance of different models--or versions of the same model--to help users analyze which model or model version is best suited for production usage.

The following phases lay the groundwork for doing a Champion/Challenger comparison.

  1. Define the evaluation metrics for the model. See Model Monitoring: Overview.

  2. Automate evaluation tests - this is done either by manually running metrics jobs (see Running a Metrics Job Manually) or through an automated MLC Process. You can build an MLC Process to automatically execute metrics tests for a particular version of a model. See Model Lifecycle Management Overview for more information.

  3. Conduct a side-by-side comparison of the test results in the Champion/Challenger page of the Command Center (see next section).


Champion/Challenger Comparison

For the previously generated metrics results (see steps 1 & 2 above), use the following steps to activate the Champion/Challenger feature in the ModelOp Center to compare test results side-by-side.


  1. Within the Evergreen Production Model Inventory, enable the “Enable champion challenger” toggle button. This will expose the “Champion/Challenger” column, allowing the user compare two or models models using the “Champion/Challenger” check boxes.


2. Hit the “Compare Models” button


3. The Champion/Challenger comparison screen will open to compare the latest Test Results for those selected models


See Model Governance: Model Management for more information about the information that is contained for each model within the Production Model Inventory.


Next Article: Model Monitoring: Overview >