Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/46850
Type: Conference paper
Title: Unifying rational models of categorization via the hierarchical Dirichlet process
Author: Griffiths, T.
Canini, K.
Sanborn, A.
Navarro, D.
Citation: Proceedings of the 29th Annual Cognitive Science Society, August 1-4 2007, Nashville, Tennessee, pp.323-328.
Publisher: Psychology Press
Publisher Place: United States
Issue Date: 2007
Conference Name: Annual Conference of the Cognitive Science Society (29th : 2007 : Nashville, Tennessee, USA)
Statement of
Responsibility: 
Thomas Griffiths, Kevin Canini, Adam Sanborn, Dan Navarro
Abstract: Models of categorization make different representational assumptions, with categories being represented by prototypes, sets of exemplars, and everything in between. Rational models of categorization justify these representational assumptions in terms of different schemes for estimating probability distributions. However, they do not answer the question of which scheme should be used in representing a given category. We show that existing rational models of categorization are special cases of a statistical model called the hierarchical Dirichlet process, which can be used to automatically infer a representation of the appropriate complexity for a given category.
Rights: © the authors
RMID: 0020077669
Appears in Collections:Psychology publications

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