Comparative Study of Density-based Clustering Algorithms

Abstract

Abstract: Data mining and exploratory data analysis deal with large datasets wherein one of the objective is to group objects such that objects falling under the same group have more similarities than the objects of two different groups, these groups are called clusters. Here similarity of objects is measured in terms of distance between the objects. The process of grouping objects is called clustering. There are numerous applications of clustering in variety of fields and data involved in each varies a lot. This has led researchers to come out with various methods and models of clustering. There are different types of clustering methods: Hierarchical, Partitioning, Density Based, Grid based and Graph Based. This paper presents a study of various methods of clustering and discusses briefly on various Density based clustering methods.