Combining artificial immune system with support vector machine for clustering analysis

被引：0

作者：

Li, Zhonghua ^{[1
]}

Tan, Hongzhou ^{[1
]}

机构：

[1] Sun Yat Sen Univ, Dept Elect & Commun Engn, Guangzhou 510275, Guangdong, Peoples R China

来源：

DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13E卷

关键词：

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Data clustering is an unsupervised machine learning method, which is widely applied to pattern recognition, spatial data analysis, image processing, economics, document categorization, web mining, etc. With the explosive increase of information, it is necessary to conduct researches in clustering and analyzing massive data. Recently, artificial immune system developed quickly due to its powerful capability of information processing. The specific mechanisms of immune system make it possible to compress data and discover patterns. Meanwhile, support vector machine is an excellent approach for classification, regression and clustering. In this paper, we proposed a novel approach to data clustering by combining artificial immune system with support vector machine. Simulation experiments were conducted on the basis of classical datasets. The results show that the approach presented in this paper is of usability.

引用

页码：1370 / 1375

页数：6

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