What are the pros and cons of using Deviance as opposed to Gini coefficient when measuring the quality of regression / classification models?
From experience, I see that people like Gini more than Deviance. I don't know the reason, but perhaps the Deviance is too sensible to the outlier, and the Gini is not. It can be inconvenient our convenient at the same time. For me, both measures should be considered at the same time.