Introduction

Data Science requires experimentation using a variety of methods, approaches, frameworks, and potentially even coding languages. Champion/Challenger is an industry standard technique to compare the performance of competing model strategies, or the performance of a recently updated model against a previous version of the same model. The Champion/Challenger feature in ModelOp Center does a side-by side comparison of the performance of different models in order to determine which model is better to promote to production.

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

1. Define the evaluation metrics for the model. See Model Efficacy Metrics and Monitoring.

2. Build evaluation tests - this is done 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 Manager Automation for more information.

3. Conduct a side-by-side comparison of the test results in the Champion/Challenger page of the Command Center.

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. In the Command Center, navigate to Models.

2. Choose the (two or more) models you would like to compare.

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3. Select the test results for each of the models

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4. You can view the metrics side-by-side to decide which model is performing better.

    

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