Bayes classifier based on self-organizing mapping neural network

被引：0
|
作者：
Zhu, SH [1 ]
Ma, L [1 ]
Lu, H [1 ]
机构：
[1] Air Force Engn Univ, Commun Engn Inst, Xian 710077, Peoples R China
来源：
2000 IEEE ASIA-PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS: ELECTRONIC COMMUNICATION SYSTEMS | 2000年
关键词：
D O I：
10.1109/APCCAS.2000.913411
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 proposes a new self-organizing learning algorithm based on isoton mapping characteristic and cluster characteristic of self-organizing mapping neural network for the Bayes classification. The algorithm is that the network is trained by the given pattern samples, so that the classification results are directly presented from the output, avoiding the errors introduced by estimation probability density function. The experiment results show the efficiency and reliability of this algorithm.
引用
收藏
页码：82 / 84
页数：3
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