""The fundamental assumption in many predictive models is that the predictors have normal distributions."
Which methods? Trees, OLS and others do not require this assumption. Could you explain? Thanks. "
"Precision is the probability of event among those that you forecast as event, and similarly for non-events. It's the bayesian posterior of accuracy, and in common usage, it's the foundation of lift tables. Accuracy is important in models…"
1) accuracy is not that interesting in a business setting. Can you give measures of precision?
2) you don't mention which classifier you used, or maybe I skipped that part.
3) in relation to 2), Owen in a 2007 paper shows…"