Clustering Ensemble Algorithm Based on Mathematical Morphology
基于数学形态学的聚类集成算法

In this paper, a clustering ensemble algorithm named CEOMM was proposed, which combines multiple clustering cores explored by different structure elements to get a desirable and correct clustering core of a data set, And then CEOMM gets the clustering of the data set based on the ensemble clustering core. Experimental results demonstrate CEOMM can cluster data with complex cluster shapes better than the classical clustering algorithms, and it can also find an optimal number of clusters. Moreover,CEOMM can discover overlapping clusters with different arbitrary shapes,because it uses different structure elements.