Literature DB >> 18083157

One or two dimensions in spontaneous classification: a simplicity approach.

Emmanuel M Pothos1, James Close.   

Abstract

When participants are asked to spontaneously categorize a set of items, they typically produce unidimensional classifications, i.e., categorize the items on the basis of only one of their dimensions of variation. We examine whether it is possible to predict unidimensional vs. two-dimensional classification on the basis of the abstract stimulus structure, by employing Pothos and Chater's simplicity model of spontaneous categorization [Pothos, E. M., & Chater, N. (2002). A simplicity principle in unsupervised human categorization. Cognitive Science, 26, 303-343]. The simplicity model provides a quantitative measure of how intuitive a particular classification is. With objects represented in two dimensions, we propose that a unidimensional classification will be preferred if it is more intuitive than all possible two-dimensional ones, and vice versa. Empirical results supporting this proposal are reported. Implications for Goodman's paradox are discussed.

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Year:  2008        PMID: 18083157     DOI: 10.1016/j.cognition.2007.11.007

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  7 in total

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5.  A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

Authors:  Kathryn L Carpenter; Andy J Wills; Abdelmalek Benattayallah; Fraser Milton
Journal:  Hum Brain Mapp       Date:  2016-05-20       Impact factor: 5.038

6.  What makes some species of milk snakes more attractive to humans than others?

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7.  The helpfulness of category labels in semi-supervised learning depends on category structure.

Authors:  Wai Keen Vong; Daniel J Navarro; Andrew Perfors
Journal:  Psychon Bull Rev       Date:  2016-02
  7 in total

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