Base rates in category learning

Abstract

Previous researchers have discovered perplexing inconsistencies in how people appear to utilize category base rates when making category judgments. In particular, D.L. Medin and S.M. Edelson (1988) found an inverse base-rate effect, in which participants tended to select a rare category when tested with a combination of conflicting cues, and M.A. Gluck and G.H. Bower (1988) reported apparent base-rate neglect, in which participants tended to select a rare category when tested with a single symptom for which objective diagnosticity was equal for all categories. This article suggests that common principles underlie both effects: First, base-rate information is learned and consistently applied to all training and testing cases. Second, the crucial effect of base rates is to cause frequent categories to be learned before rare categories so that the frequent categories are encoded by their typical features and the rare categories are encoded by their distinctive features. Four new experiments provide evidence consistent with those principles. The principles are formalized in a new connectionist model that can rapidly shift attention to distinctive features.