Heterogeneous Density Based Spatial Clustering of Application With Noise

The DBSCAN algorithm is a popular algorithm in Data Mining field as it has the ability to mine the noiseless arbitrary shape Clusters in an elegant way. As the original DBSCAN algorithm expand the Cluster based on the core object condition, it doesn't have the intelligence to mine the clusters which have different densities and these clusters may or may not be separated by the sparse region. In this paper, the authors propose a new algorithm for mining the density based clusters and the algorithm is intelligent enough to mine the clusters with different densities.