Training RBF neural networks on unbalanced data

被引：0
|
作者：
Fu, XJ [1 ]
Wang, LP [1 ]
Chua, KS [1 ]
Chu, F [1 ]
机构：
[1] Inst High Performance Comp, Singapore 117528, Singapore
来源：
ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE | 2002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：
This paper presents a new algorithm for the construction and training of an RBF neural network with unbalanced data. In applications, minority classes with much fewer samples are often present in data sets. The learning process of a neural network usually is biased towards classes with majority populations. Our study focused on improving the classification accuracy of minority classes while maintaining the overall classification performance.
引用
收藏
页码：1016 / 1020
页数：5
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