基于超球支持向量机的兼类文本分类算法研究  

Study on multi-class text classification algorithm based on hyper-sphere support vector machines

作　　者：秦玉平[1,2] 王秀坤[1] 李祥纳[3] 王春立[1] 

机构地区：[1]大连理工大学电子与信息工程学院 [2]渤海大学信息科学与工程学院,辽宁锦州121000 [3]渤海大学信息科学与工程学院

出　　处：《计算机工程与应用》2008年第19期166-168,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60603023);国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2001CCA00700)

摘　　要：针对兼类文本,提出了一种分类算法。对属于同一类别的文本,利用超球支持向量机在特征空间中求得一个能包围该类尽可能多文本的最小超球,使各类文本之间通过超球分隔开,达到分类效果。对待分类文本,计算它到各超球球心的距离,根据距离判定该文本所属的类别。实验结果证明,该算法不仅具有较快的分类速度,而且具有较高的分类精度。To multi-class text,a classification algorithm based on hyper-sphere support vector machines is proposed in this paper.Hyper-sphere support vector machine is used to get the smallest hyper-sphere in feature space that contains most texts of a class,which can divide the class texts from others.For the text to be classified,the distances from it to the centre of every hyper-sphere are used to confirm the classes that the text belongs to.The experimental results show that the algorithm not only has a faster pefformance on classification speed,but also has a higher performance on classification precision.

关 键 词：支持向量机 超球 兼类 分类 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]