Maximum density clustering algorithm
Jing Wang · Journal of the Graduate School of the Chinese Academy of Sciences · 2009
This paper proposes a new clustering algorithm named maximum density clustering algorithm(MDCA). In MDCA the concept of density is introduced to identify the count of clusters automatically.By selecting the densest object as the threshold, densities of those objects around the densest object are reviewed to decide the partition of basic blocks. Then the basic blocks are merged to form clusters of arbitrary shape. Experiments show that the ability and validity of MDCA in processing unknown datasets are all better than traditional partition-based clustering algorithms.