Cluster ensemble selection based on relative validity indexes
Abstract—Cluster ensemble selection based on relative validity indexes. Selective clustering ensemble is usually based on the reference partition to select members of the ensemble. General method of generating reference partition is to use preliminary ensemble results, < Final Year Projects > yet it cannot eliminate the influence of the inferior clustering partitions and the final clustering result is not satisfactory. In order to solve this problem, the paper proposes a new selective clustering ensemble algorithm. The new algorithm includes two points :(1) selecting the best reference partition based on clustering validity evaluation, (2)putting forward the new selection strategy and the method of member’s weight. The experimental results show that the new algorithm is effective and clustering accuracy could be significantly improved.