Abstract: 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 performance on classification speed，but also has a higher performance on classification precision.

Key words: support vector machines, hyper-sphere, multi-class, classification

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。

关键词: 支持向量机, 超球, 兼类, 分类