Comparing categorization models.
Four experiments are presented that competitively test rule- and exemplar-based models of human categorization behavior. Participants classified stimuli that varied on a unidimensional axis into 2 categories. The stimuli did not consistently belong to a category; instead, they were probabilistically assigned. By manipulating these assignment probabilities, it was possible to produce stimuli for which exemplar- and rule-based explanations made qualitatively different predictions. F. G. Ashby and J. T. Townsend's (1986) rule-based general recognition theory provided a better account of the data than R. M. Nosofsky's (1986) exemplar-based generalized context model in conditions in which the to-be-classified stimuli were relatively confusable. However, generalized context model provided a better account when the stimuli were relatively few and distinct. These findings are consistent with multiple process accounts of categorization and demonstrate that stimulus confusion is a determining factor as 10 which process mediates categorization.
Department of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, US. jeff@banta.psyc.missouri.edu
Jeffrey N
JN
Rouder
Roger
R
Ratcliff
D003657:Decision Making; D003661:Decision Support Techniques; D006801:Humans; D008960:Models, Psychological; D011336:Probability; D011582:Psychological Theory