CFSFDP (clustering by fast search and find of density peaks) is recently developed densitybasedclustering algorithm. Compared to DBSCAN, it needs less parameters and iscomputationally cheap for its non-iteration. Alex. at al have demonstrated its power by manyapplications. However, CFSFDP performs not well when there are more than one density peakfor one cluster, what we name as "no density peaks". In this paper, inspired by the idea of ahierarchical clustering algorithm CHAMELEON, we propose an extension of CFSFDP,E_CFSFDP, to adapt more applications. In particular, we take use of original CFSFDP togenerating initial clusters first, then merge the sub clusters in the second phase. We haveconducted the algorithm to several data sets, of which, there are "no density peaks". Experimentresults show that our approach outperforms the original one due to it breaks through the strictclaim of data sets.
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