Firstly, it is not a valid argument to claim that because subjects can't pick out the features they use to categories, they are not using features. Most of our methods of doing cognitive tasks are not evident by introspection. Also Rosch confuses ontic metaphysical questions with epistemic questions. The psychologist is interested in how we actually categorize, and so there is little point focussing on the grey areas, where people are not sure which category to put an item in, as this leads on to questions about what things really are. Rosch's prototype idea can also be criticised on the basis that it doesn't really give any thoughts to the mechanisms that lie behind our ability to categorize.
Any mechanism has to ignore irrelevant features and pay attention to relevant, invariant features.
This can be illustrated by the ugly duckling theorem, which proves that 7 white geese and 1 black swan are all equally different if every feature is equally weighted. Computationalists think we categorize on the basis of rules. With unsupervised learning, neural nets will sort items into categories without feedback, this really just enhances natural contours. With supervised learning, neural nets use the feedback signal to pick out the invariant or salient features. The categorization that we have enables us to ground symbols in our capacity to use them.