A Survey on Density Based Clustering Algorithms for Mining Large Spatial Databases
Density based clustering algorithm is one of the primary methods for clustering in data mining. The clusters which are formed based on the density are easy to understand and it does not limit itself to the shapes of clusters. This paper gives a detailed survey of the existing density based algorithms namely DBSCAN, VDBSCAN, DVBSCAN, ST-DBSCAN and DBCLASD based on the essential parameters needed for a good clustering algorithm. The authors analyze the algorithms in terms of the parameters essential for creating meaningful clusters.