基于Chameleon算法和谱平分法的聚类新方法

在分析传统的聚类算法优越性和存在不足的基础上，基于Chameleon算法和谱平分法的思想提出了一种新的聚类方法。相比传统聚类算法而言此算法克服了如k—means算法、EM算法等传统聚类算法在聚类不为凸的样本空间时容易陷入局部最优的缺点，能在任意形状的样本空间上聚类，且收敛于全局最优解，并且可以降低噪声和离群点的影响，提高了算法的有效性。在UCI数据集和5个特殊的二维数据点组成的数据集上进行了实验，证明了本方法的有效性。

A New Clustering Method Based on the Chameleon Algorithm and the Spectral Bisection Method

With analysis of advantages and disadvantages of traditional clustering algorithms,we proposed a new clustering method based on the Chameleon algorithm and the spectral bisection method.Unlike traditional clustering algorithms,this algorithm overcomes a disadvantage of some traditional clustering algorithms such as the k-means algorithm and the EM algorithm,that is,they are prone to local optimum when clustering on a nonconvex sample space.It is capable of clustering on a sample space of any shape and conve...