基于类内差异和类间重叠的有效性函数

模糊C-均值(FCM)聚类算法的一个主要问题是需要事先确定聚类的数目,为此定义了类内差异度和类间重叠度来分别度量同一个聚类中数据的相似度和不同聚类间的分离程度,进而基于这两个度量提出一个新的有效性函数用于判定最佳聚类数目。实验结果表明,该有效性函数能有效地判定聚类数目,并且有较好的鲁棒性。

A new validity index based on intra-cluster variation and inter-cluster overlap

The determination of cluster number is still an open problem for fuzzy C-means clustering.In this paper,a new validity index is proposed to evaluate partition and determine the optimal number of clusters for fuzzy clustering.In a good partition,the similarities of patterns in a cluster should be maximized and the clusters should be well separated.Intra-cluster variation and intercluster overlap are defined to measure the similarities within a cluster and the separation between clusters respectively.The vali...