Literature DB >> 11394680

Prototypes in category learning: the effects of category size, category structure, and stimulus complexity.

J P Minda1, J D Smith.   

Abstract

Although research in categorization has sometimes been motivated by prototype theory, recent studies have favored exemplar theory. However, some of these studies focused on small, poorly differentiated categories composed of simple, 4-dimensional stimuli. Some analyzed the aggregate data of entire groups. Some compared powerful multiplicative exemplar models to less powerful additive prototype models. Here, comparable prototype and exemplar models were fit to individual-participant data in 4 experiments that sampled category sets varying in size, level of category structure, and stimulus complexity (dimensionality). The prototype model always fit the observed data better than the exemplar model did. Prototype-based processes seemed especially relevant when participants learned categories that were larger or contained more complex stimuli.

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Year:  2001        PMID: 11394680

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  55 in total

1.  Expanding the search for a linear separability constraint on category learning.

Authors:  M Blair; D Homa
Journal:  Mem Cognit       Date:  2001-12

2.  Fruits and vegetables categorized: an application of the generalized context model.

Authors:  Tim Smits; Gert Storms; Yves Rosseel; Paul De Boeck
Journal:  Psychon Bull Rev       Date:  2002-12

3.  Comparisons between exemplar similarity and mixed prototype models using a linearly separable category structure.

Authors:  Roger D Stanton; Robert M Nosofsky; Safa R Zaki
Journal:  Mem Cognit       Date:  2002-09

4.  A single-system interpretation of dissociations between recognition and categorization in a task involving object-like stimuli.

Authors:  S R Zaki; R M Nosofsky
Journal:  Cogn Affect Behav Neurosci       Date:  2001-12       Impact factor: 3.282

5.  As easy to memorize as they are to classify: the 5-4 categories and the category advantage.

Authors:  Mark Blair; Don Homa
Journal:  Mem Cognit       Date:  2003-12

6.  Computational Models Inform Clinical Science and Assessment: An Application to Category Learning in Striatal-Damaged Patients.

Authors:  W Todd Maddox; J Vincent Filoteo; Dagmar Zeithamova
Journal:  J Math Psychol       Date:  2010-02-01       Impact factor: 2.223

7.  Geometric and featural representations in semantic concepts.

Authors:  Wolf Vanpaemel; Timothy Verbeemen; Matthew Dry; Tom Verguts; Gert Storms
Journal:  Mem Cognit       Date:  2010-10

8.  Deferred feedback sharply dissociates implicit and explicit category learning.

Authors:  J David Smith; Joseph Boomer; Alexandria C Zakrzewski; Jessica L Roeder; Barbara A Church; F Gregory Ashby
Journal:  Psychol Sci       Date:  2013-12-13

9.  Learning categories by making predictions: an investigation of indirect category learning.

Authors:  John Paul Minda; Brian H Ross
Journal:  Mem Cognit       Date:  2004-12

10.  Sex Differences in Symptom Phenotypes Among Patients With Acute Myocardial Infarction.

Authors:  John E Brush; Harlan M Krumholz; Erich J Greene; Rachel P Dreyer
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2020-02-17
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