Fuzzy labeled self-organizing map for classification of spectra

被引：0

作者：

Villmann, T. ^{[1
]}

Schleif, F. -M. ^{[1
]}

Merenyi, E. ^{[2
]}

Hammer, B. ^{[3
]}

机构：

[1] Univ Leipzig, Dept Med, Leipzig, Germany

[2] Rice Univ, Houston, TX 77251 USA

[3] Tech Univ Clausthal, Inst Comp Sci, Clausthal Zellerfeld, Germany

来源：

COMPUTATIONAL AND AMBIENT INTELLIGENCE | 2007年 / 4507卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We extend the self-organizing map to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning of fuzzy labeled or partially contradictory data is possible. On the other hand, class similarities may be detected. Further, we integrate the parametrized functional metric as data similarity measure into the approach. Parametrization of this functional metric allows relevance learning for efficient classification and feature selection.

引用

页码：556 / +

页数：2

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