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Monitoring adaptive models

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The predictive performance and success rate of individual adaptive models provide information that can help business users and decisioning consultants to refine the Next-Best-Actions of the company. It is a regular data scientist task to inspect the health of the adaptive models and share the findings with the business. 

After completing this module, you should be able to:

Name the key metrics of adaptive models visualized in the bubble chart
Customize the bubble chart by filtering
Inspect active and inactive predictors
Inspect individual predictors
Explain how predictors with similar predictive performance are grouped
Examine the propensity distribution for the whole model
Examine the trend for the whole model

Available in the following mission:

Data Scientist v2

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