Relations between exemplar-similarity and likelihood models of classification
Journal of Mathematical PsychologyPublished 1 December 1990
Robert M. Nosofsky
Citations138
SJR quartileQ2
SJR score0.74
SNIP1.10
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TL;DR
It is shown that for category distributions defined over independent dimensions, general versions of the context model and Estes' similarity-likelihood model are formally identical.
Abstract
The similarity choice model of identification (Luce, 1963; Shepard, 1957) and the context model of categorization (Medin & Schaffer, 1978; Nosofsky, 1986) are shown to be closely related to a variety of likelihood-based models. In particular, it is shown that: (1) for category distributions defined over independent dimensions, general versions of the context model and Estes' (1986) similarity-likelihood model are formally identical; (2) the context model and similarity choice model can be given interpretations as exemplar-based likelihood models; (3) an independent feature addition-deletion model is a special case of the similarity choice model; and (4) a perception/likelihood-based decision model of identification generates predictions that are characterizable by the similarity choice model.
Keywords
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