A New Clustering Method Based on References, Density and Neural Network

In this paper, a new clustering algorithm that is called RDVS (clustering using references and density by ViSOM) is presented to overcome the shortcomings of clustering methods based on density or neural network. The creativity of RDVS is capturing the shape and extent of a cluster by references and their densities, and then analyzes them by ViSOM. RDVS keeps the ability of density-based clustering method's good features and it can give a visual clustering results. Both theory analysis and experimental results confirm that RDVS can discover clusters with arbitrary shape and is insensitive to noise data, and its executing efficiency is much higher than ViSOM