期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2016
卷号：5
期号：7
页码：2168-2172
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Density -based clustering methods are one of the important category of clustering methods that are able to identify areas with dense clusters of different shape and size.One of the basic and simple methods in this group is DBSCAN . This algorithm clusters dataset based on two received parameters from the user one is min points and second is the radius. One of the disadvantages of DBSCAN is its inability in identifying clusters with different densities in a dataset. In this paper, we are carrying out a survey to find out various algorithms related to DBSCAN and also other algorithm which can be used to detect clusters and outliers. Also their capability to detect cluster with varied density will be surved. Here multi density data set cluster detecting algorithm will be preffered.
