How do I interpret driver rankings for my propensity or regression model?

Also known as a feature importance chart in data science, the driver rankings chart for a propensity or regression model shows the relative importance of each independent variable in generating a model prediction. It can be loosely interpreted as the share of variance explained by the model that can be attributed to a specific independent variable. 

In practice it is a helpful way to rank which drivers (independent variables) contribute most to a model prediction on average. 

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