基于原型的规则——一种理解数据的新方法

Wlodzislaw Duch, K. Grudzinski
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引用次数: 32

摘要

逻辑规则并不是理解数据结构的唯一方法。基于原型的规则使用优化的相似性度量来评估与一小组原型的相似性。这种规则包括作为特例的清晰逻辑规则和模糊逻辑规则,从心理学的角度来看,这是一种自然的分类方式。描述了从训练集中选择好的原型的消除过程。在几个数据集上的说明性应用表明,一些原型确实可以解释数据结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prototype based rules-a new way to understand the data
Logical rules are not the only way to understand the structure of data. Prototype-based rules evaluate similarity to a small set of prototypes using optimized similarity measures. Such rules include crisp and fuzzy logic rules as special cases and are natural way of categorization from psychological point of view. An elimination procedure selecting good prototypes from a training set has been described. Illustrative applications on several datasets show that a few prototypes may indeed explain the data structure.
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