For my (binary) classification problem I'm developing several features and tune them with ROC curves. At some point, I want to combine them with in classifier. How well should the features perform, for example in terms of AUC, to discriminate my data "good enough" and build a powerful classifier out of them?
This is a very general question, but maybe you know interesting literature on that.