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类别学习中的基础概率

Base rates in category learning.

作者信息

Kruschke J K

机构信息

Department of Psychology, Indiana University, Bloomington 47405, USA.

出版信息

J Exp Psychol Learn Mem Cogn. 1996 Jan;22(1):3-26. doi: 10.1037//0278-7393.22.1.3.

DOI:10.1037//0278-7393.22.1.3
PMID:8648289
Abstract

Previous researchers have discovered perplexing inconsistencies in how people appear to utilize category base rates when making category judgments. In particular, D.L. Medin and S.M. Edelson (1988) found an inverse base-rate effect, in which participants tended to select a rare category when tested with a combination of conflicting cues, and M.A. Gluck and G.H. Bower (1988) reported apparent base-rate neglect, in which participants tended to select a rare category when tested with a single symptom for which objective diagnosticity was equal for all categories. This article suggests that common principles underlie both effects: First, base-rate information is learned and consistently applied to all training and testing cases. Second, the crucial effect of base rates is to cause frequent categories to be learned before rare categories so that the frequent categories are encoded by their typical features and the rare categories are encoded by their distinctive features. Four new experiments provide evidence consistent with those principles. The principles are formalized in a new connectionist model that can rapidly shift attention to distinctive features.

摘要

先前的研究人员发现,在人们进行类别判断时,他们在如何利用类别基础概率方面存在令人困惑的不一致性。具体而言,D.L. 梅丁和S.M. 埃德尔森(1988年)发现了一种逆基础概率效应,即当参与者面对相互冲突的线索组合进行测试时,他们倾向于选择罕见类别;而M.A. 格鲁克和G.H. 鲍尔(1988年)报告了明显的基础概率忽视现象,即当参与者面对单一症状进行测试时(对所有类别而言,该症状的客观诊断性相同),他们倾向于选择罕见类别。本文认为,这两种效应都有共同的原则:第一,基础概率信息是通过学习获得的,并始终应用于所有训练和测试案例。第二,基础概率的关键作用是使常见类别在罕见类别之前被学习,以便常见类别通过其典型特征进行编码,而罕见类别通过其独特特征进行编码。四项新实验提供了与这些原则一致的证据。这些原则在一个新的联结主义模型中得到了形式化,该模型能够迅速将注意力转移到独特特征上。

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