Maximum entropy interpretation of decision bound and context models of categorization

DOI10.1006/jmps.1994.1024zbMath0801.92030OpenAlexW1984647418MaRDI QIDQ1336997

In Jae Myung

Publication date: 8 November 1994

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmps.1994.1024

zbMATH Keywords

decision bound modelscontext model of categorizationsimilarity rulesbinary featurescontinuous featuresexponential-city- block-similarity rulesGaussian-Euclidean multidimensional scalingmaximum entropy inferencemultiplicative similarity rule

Mathematics Subject Classification ID

Measures of information, entropy (94A17) Psychophysics and psychophysiology; perception (91E30) Mathematical psychology (91E99)

Related Items (4)

Probabilistic choice (models) as a result of balancing multiple goals ⋮ Mixture models of categorization ⋮ Generalization of the theory of signal detectability to \(n\)-event \(m\)-dimensional forced-choice tasks. ⋮ Identification model based on the maximum information entropy principle

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