Predicting features for members of natural categories when categorization is uncertain.
Predicting features for members of natural categories when categorization is uncertain.
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当分类不确定时预测自然类别成员的特征。
DOI：
10.1037//0278-7393.21.3.646
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
Murphy,GL
中科院分区：
文献类型：
--
作者：
Malt,BC;Ross,BH;Murphy,GL
概念的一个重要功能是允许预测看不见的特征。贝叶斯对特征预测的解释表明，当人们判断物体具有特征的可能性时，他们会考虑物体可能属于的所有类别。判断和决策文献表明，他们可能会使用一种更简单的启发式方法，只考虑最有可能的类别。在3个实验中，没有证据表明，参与者考虑到替代类别，以及最有可能的一个，当他们判断特征概率熟悉的对象在有意义的上下文中。这些结果，以及GL Murphy和BH Ross（1994）的结果表明，尽管人们可能会在某些有限的情况下考虑替代类别，但他们通常不会。为什么使用替代类别可能是相对罕见的原因进行了讨论，并在何种条件下，人们可以考虑替代类别的概述。（PsycInfo数据库记录（c）2016阿帕，保留所有权利）
An important function of concepts is to allow the prediction of unseen features. A Bayesian account of feature prediction suggests that people will consider all the categories an object could belong to when they judge the likelihood that the object has a feature. The judgment and decision literature suggests that they may instead use a simpler heuristic in which they consider only the most likely category. In 3 experiments, no evidence was found that participants took into account alternative categories as well as the most likely one when they judged feature probabilities for familiar objects in meaningful contexts. These results, in conjunction with those of GL Murphy and BH Ross (1994), suggest that although people may consider alternative categories in certain limited situations, they often do not. Reasons for why the use of alternative categories may be relatively rare are discussed, and conditions under which people may take alternative categories into account are outlined.(PsycINFO Database Record (c) 2016 APA, all rights reserved)