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COGSCI
2002

A simplicity principle in unsupervised human categorization

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A simplicity principle in unsupervised human categorization
We address the problem of predicting how people will spontaneously divide into groups a set of novel items. This is a process akin to perceptual organization. We therefore employ the simplicity principle from perceptual organization to propose a simplicity model of unconstrained spontaneous grouping. The simplicity model predicts that people would prefer the categories for a set of novel items that provide the simplest encoding of these items. Classification predictions are derived from the model without information either about the number of categories sought or information about the distributional properties of the objects to be classified. These features of the simplicity model distinguish it from other models in unsupervised categorization (where, for example, the number of categories sought is determined via a free parameter), and we discuss how these computational differences are related to differences in modeling objectives. The predictions of the simplicity model are validated...
Emmanuel M. Pothos, Nick Chater
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2002
Where COGSCI
Authors Emmanuel M. Pothos, Nick Chater
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