A supervised self-organizing map for structured data

被引：0

作者：

Hagenbuchner, M ^{[1
]}

Tsoi, AC ^{[1
]}

Sperduti, A ^{[1
]}

机构：

[1] Univ Wollongong, Fac Informat, Wollongong, NSW, Australia

来源：

ADVANCES IN SELF-ORGANISING MAPS | 2001年

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：

A self organizing map (SOM) for processing of structured data, using an unsupervised learning approach, called SOM-SD, has recently been proposed. Here, we suggest a new version of SOM, using the supervised learning approach. We compare the supervised version and the unsupervised version of SOM-SD on a benchmark problem involving visual patterns. As may be expected, the supervised version is able to solve the classification problem using very compact networks.

引用

页码：21 / 28

页数：8

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