Fuzzy labeled self-organizing map with label-adjusted prototypes

被引：0

作者：

Villmann, Thomas ^{[1
]}

Seiffert, Udo

Schleif, Frank-Michael

Bruess, Cornelia

Geweniger, Tina

Hammer, Barbara

机构：

[1] Univ Leipzig, Dept Med, D-7010 Leipzig, Germany

[2] IPK Gatersleben, Pattern Recognit Grp, Gatersleben, Germany

[3] BRUKER Daltonik Leipzig, Numer Toolbox Grp, Leipzig, Germany

[4] Univ Leipzig, Inst Comp Sci, D-7010 Leipzig, Germany

[5] Tech Univ Clausthal, Inst Comp Sci, D-3392 Clausthal Zellerfeld, Germany

来源：

ARTIFICIAL NEURAL NETWORKS IN PATTERN RECOGNITION, PROCEEDINGS | 2006年 / 4087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 (SOM) in the form as proposed by Heskes to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning with fuzzy labeled or partially contradictory data is possible. On the other hand, the integration of labeling into the location of prototypes in a SOM leads to a visualization of those parts of the data relevant for the classification.

引用

页码：46 / 56

页数：11

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