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
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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.
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页码：46 / 56
页数：11
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