The research on selective clustering ensemble algorithm based on fractal dimension and projection

Selective clustering ensemble algorithm can eliminate the inferior quality clustering member's influence and can achieve a better clustering solution relative to the clustering ensemble algorithm. For high dimensional data clustering, in this paper, a novel selective clustering ensemble algorithm based on fractal dimension and projection is proposed. Firstly, the clustering members are generated by the clustering algorithm based on fractal dimension and projection to realize dimension reduction and clustering; then the selection strategy based on the best reference partition is used to produce the components of the ensemble system in order to pick part of high quality cluster members to realize ensemble by using weighted Co-association matrix, and get the final clustering results at last. The experimental results on UCI data set verify the validity of the proposed algorithm for dealing with high dimensional data clustering. The new algorithm is able to achieve statistically significant performance improvement over other clustering algorithms. ©, 2015, Binary Information Press. All right reserved.