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Formal Approaches in Categorization.

Author: Emmanuel M Pothos; Andy J Wills
Publisher: Leiden : Cambridge University Press, 2011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Brings together the prominent approaches to categorization, providing an evaluation of the state of the art of formal categorization research.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Pothos, Emmanuel M.
Formal Approaches in Categorization.
Leiden : Cambridge University Press, ©2011
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Emmanuel M Pothos; Andy J Wills
ISBN: 9780511859106 0511859104 1283006227 9781283006224
OCLC Number: 703137554
Notes: Cover; Half-title; Title; Copyright; Contents; Figures; Tables; Contributors; 1 Introduction; 2 The generalized context model: an exemplar model of classification; 3 Prototype models of categorization: basic formulation, predictions, and limitations; 4 COVIS; 5 Semantics without categorization; 6 Models of attentional learning; 7 An elemental model of associative learning and memory; 8 Nonparametric Bayesian models of categorization; 9 The simplicity model of unsupervised categorization; 10 Adaptive clustering models of categorization.
11 Cobweb models of categorization and probabilistic concept formation12 The knowledge and resonance (KRES) model of category learning; 13 The contribution (and drawbacks) of models to the study of concepts; 14 Formal models of categorization: insights from cognitive neuroscience; 15 Comments on models and categorization theories: the razor's edge; Index.
Description: 1 online resource (350 pages)
Contents: Cover; Half-title; Title; Copyright; Contents; Figures; Tables; Contributors; 1 Introduction; 2 The generalized context model: an exemplar model of classification; 3 Prototype models of categorization: basic formulation, predictions, and limitations; 4 COVIS; 5 Semantics without categorization; 6 Models of attentional learning; 7 An elemental model of associative learning and memory; 8 Nonparametric Bayesian models of categorization; 9 The simplicity model of unsupervised categorization; 10 Adaptive clustering models of categorization.

Abstract:

Brings together the prominent approaches to categorization, providing an evaluation of the state of the art of formal categorization research.

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