Hierarchical Clustering Ensemble Algorithm Based Association Rules

Present, there is more research on supervised clustering ensemble algorithm, but the research on unsupervised clustering ensemble is studied less. In order to partition data points under fully unsupervised conditions, the hierarchical clustering ensemble algorithm based on association rules (HCEAR) is proposed in this paper. The optimal number of clusters is determined by average degree of clustering using distribution of all clustering memberships and support degree of association rules. Then variation of the hierarchical clustering algorithm was adopted for best partition. Related theories ware proved detail in this paper. Finally, the HCEAR is applied in instance and results show it is effective.