The Research of Classification based on Improved RBF Neural Network

被引：1

作者：

Wang Lin-shuang ^{[1
]}

Zhou Li-juan ^{[1
]}

Ge Xue-bin ^{[1
]}

Shi Qian ^{[1
]}

机构：

[1] Capital Normal Univ, Informat Engn Coll, Beijing, Peoples R China

来源：

ICCSSE 2009: PROCEEDINGS OF 2009 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION | 2009年

关键词：

RBF neural network; classification; Data Mining;

D O I：

10.1109/ICCSE.2009.5228157

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The approximation accuracy of RBF network constructed by the incremental learning algorithm to the target was not high. For function approximation or other requirements of high accuracy, such accuracy of RBF network model can not meet the requirements. We have improved this network model focused on three aspects to improve the bottleneck, and have an experiment and comparatively analyze these improvements algorithm on an UCI database, the experimental results show that the improved algorithm has better performances.

引用

页码：792 / 796

页数：5

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