Literature DB >> 8934845

Selective attention and the formation of linear decision boundaries.

S C McKinley1, R M Nosofsky.   

Abstract

Classification experiments were designed to compare the predictions of a linear decision bound model with those of an exemplar-similarity model incorporating an explicit selective attention mechanism. Linear boundaries could account for the data only in tasks involving separable dimension stimuli and where the boundary separating the categories was orthogonal to the psychological dimensions. Linear boundaries provided poor fits to the classification data in situations involving integral dimensions or when the boundary needed to be oriented in oblique directions in the space. The results were consistent with the selection-attention assumptions embodied in the exemplar model. It was argued that similar assumptions about selective attention need to be incorporated within decision bound models.

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Year:  1996        PMID: 8934845     DOI: 10.1037//0096-1523.22.2.294

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  13 in total

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

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3.  Recognition memory for realistic synthetic faces.

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Journal:  Mem Cognit       Date:  2007-09

4.  Knowledge partitioning in categorization: boundary conditions.

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Journal:  Mem Cognit       Date:  2006-12

5.  Generalization and similarity in exemplar models of categorization: insights from machine learning.

Authors:  Frank Jäkel; Bernhard Schölkopf; Felix A Wichmann
Journal:  Psychon Bull Rev       Date:  2008-04

6.  Information-processing architectures in multidimensional classification: a validation test of the systems factorial technology.

Authors:  Mario Fific; Robert M Nosofsky; James T Townsend
Journal:  J Exp Psychol Hum Percept Perform       Date:  2008-04       Impact factor: 3.332

7.  Perceptual dimensions influence auditory category learning.

Authors:  Casey L Roark; Lori L Holt
Journal:  Atten Percept Psychophys       Date:  2019-05       Impact factor: 2.199

8.  Similarity relations in visual search predict rapid visual categorization.

Authors:  Krithika Mohan; S P Arun
Journal:  J Vis       Date:  2012-10-23       Impact factor: 2.240

9.  Observation versus classification in supervised category learning.

Authors:  Kimery R Levering; Kenneth J Kurtz
Journal:  Mem Cognit       Date:  2015-02

10.  Lure similarity affects visual episodic recognition: detailed tests of a noisy exemplar model.

Authors:  Michael J Kahana; Feng Zhou; Aaron S Geller; Robert Sekuler
Journal:  Mem Cognit       Date:  2007-09
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