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Similarity, distance, and categorization: a discussion of Smith's (2006) warning about "colliding parameters".

作者信息

Navarro Daniel J

机构信息

School of Psychology, University of Adelaide, Adelaide, South Australia, Australia.

出版信息

Psychon Bull Rev. 2007 Oct;14(5):823-33. doi: 10.3758/bf03194107.

DOI:10.3758/bf03194107
PMID:18087945
Abstract

The idea that categorization decisions rely on subjective impressions of similarities between stimuli has been prevalent in much of the literature over the past 30 years and has led to the development of a large number of models that apply some kind of decision rule to similarity measures. A recent article by Smith (2006) has argued that these similarity-choice models of categorization have a substantial design flaw, in which the similarity and the choice components effectively cancel one another out. As a consequence of this cancellation, it is claimed, the relationship between distance and category membership probabilities is linear in these models. In this article, I discuss these claims and show mathematically that in those cases in which it is sensible to discuss the relationship between category distance and category membership at all, the function relating the two is approximately logistic. Empirical data are used to show that a logistic function can be observed in appropriate contexts.

摘要

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3
Global model analysis by parameter space partitioning.通过参数空间划分进行全局模型分析。
Psychol Rev. 2006 Jan;113(1):57-83. doi: 10.1037/0033-295X.113.1.57.
4
Modeling individual differences in cognition.模拟认知中的个体差异。
Psychon Bull Rev. 2005 Aug;12(4):605-21. doi: 10.3758/bf03196751.
5
Assessing the distinguishability of models and the informativeness of data.评估模型的可区分性和数据的信息量。
Cogn Psychol. 2004 Aug;49(1):47-84. doi: 10.1016/j.cogpsych.2003.11.001.
6
Toward a method of selecting among computational models of cognition.迈向一种在认知计算模型中进行选择的方法。
Psychol Rev. 2002 Jul;109(3):472-91. doi: 10.1037/0033-295x.109.3.472.
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The psychometric function: I. Fitting, sampling, and goodness of fit.心理测量函数:I. 拟合、抽样与拟合优度。
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