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基于范例的泛化评估与分类信息的抽象

Evaluation of exemplar-based generalization and the abstraction of categorical information.

作者信息

Busemeyer J R, Dewey G I, Medin D L

出版信息

J Exp Psychol Learn Mem Cogn. 1984 Oct;10(4):638-48. doi: 10.1037//0278-7393.10.4.638.

Abstract

This article reformulates and reanalyzes a problem originally put forth by Homa, Sterling, and Trepel (1981). The question is whether a pure, exemplar-based abstraction process is an adequate model of category learning or whether it is necessary to postulate an additional prototype-abstraction process. Based on quantitative discrepancies from a pure, exemplar-based model, Homa et al. argued that it was necessary to recognize the operation of a prototype-abstraction process in order to fully explain their results. However, Homa et al. never actually fit the exemplar plus prototype model to the data to determine if indeed the additional prototype process could explain the deviations from the pure exemplar model. The present article compared the pure exemplar model with a mixed (exemplar plus prototype) model and did not find consistent evidence requiring the postulation of an additional prototype-abstraction process. These results point out the difficulty of distinguishing alternative classification models and underscore the need for careful analytic work in this area.

摘要

本文重新阐述并重新分析了一个最初由霍马、斯特林和特雷佩尔(1981年)提出的问题。问题在于,纯粹基于范例的抽象过程是否是类别学习的充分模型,或者是否有必要假定一个额外的原型抽象过程。基于与纯粹基于范例的模型的定量差异,霍马等人认为,为了充分解释他们的结果,有必要认识到原型抽象过程的运作。然而,霍马等人从未实际将范例加原型模型拟合到数据中,以确定额外的原型过程是否确实能够解释与纯粹范例模型的偏差。本文将纯粹范例模型与混合(范例加原型)模型进行了比较,并未发现一致的证据表明需要假定一个额外的原型抽象过程。这些结果指出了区分替代分类模型的困难,并强调了在这一领域进行仔细分析工作的必要性。

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