Acquisition of category-level information can be based on experience with category members (induced) as well as on direct presentation of prototypical values (given). To investigate the effects of these two types of information, a relational coding model of categorization was developed in which classification is based on a mixture of exemplar and prototype information. In two experiments, subjects learned about two ill-defined categories. Stimuli were geometric shapes varying along four binary-valued dimensions. For three groups of subjects, training consisted of (a) experience with exemplars only, (b) learning prototype values followed by exemplar experience, or (c) learning prototype values concurrently with exemplar experience. Following training, all subjects received classification tests on prototype values as well as on old and new exemplars. By varying the relative use of prototype and exemplar information, the mixture model accurately accounted for category judgements in all three groups. For subjects directly presented with prototype values, classification was based on a mixture of similarity to prototypes and to stored exemplars. In contrast, subjects who only received experience with exemplars appeared to base their category judgements solely on similarity to stored exemplars, even though they could accurately judge the prototype values. The two components of the mixture model are related to subjects' classification strategies and the nature of abstracted, category-level information.