Hybrid SOM and fuzzy integral frameworks for fuzzy classification

A. Soria-Frisch
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引用次数: 7

Abstract

The construction of fuzzy measures in the fuzzy integral, which is considered to be the crucial point for the extended utilization of this fusion methodology, is attained in the here presented paper through a Self-Organizing Map (SOM). This fact can improve the performance in the fuzzy measure assessment specially in high-dimensional feature spaces. Different methodologies for knowledge discovery related to the SOM paradigm are taken into consideration in order to achieve the assessment of the fuzzy measure coefficients. Furthermore an overview of the utilization of the fuzzy integral in classification problems is given. Finally two hybrid frameworks considering the SOM and the fuzzy integral are presented and used for fuzzy classification.
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模糊分类的混合SOM和模糊积分框架
本文通过自组织映射(SOM)实现了模糊积分中模糊测度的构造,这是该融合方法推广应用的关键。这一事实可以提高模糊测度评价的性能,特别是在高维特征空间中。考虑了与SOM范式相关的知识发现的不同方法,以实现模糊度量系数的评估。此外,还概述了模糊积分在分类问题中的应用。最后提出了考虑SOM和模糊积分的混合框架,并将其用于模糊分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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