基于支持向量机的无监督聚类算法研究

Study on algorithm of non-monitor clustering based on support vector machines

分析了支持向量机在解决无监督分类问题上的不足,提出一种基于支持向量机思想的最大间距的聚类新方法。实验结果表明,该算法能成功地解决很多非监督分类问题。

This paper analyzes the ability of Support Vector Machinex（SVM） in dealing with the unsupervised learning problem, and proposes a new method of clustering with maximal margin based on the idea of SVM.In the experiment aspects,the results shows that this algorithm can deal with the unsupervised learning problem successfully.