COMPARATIVE STUDY OF DENSITY-BASED CLUSTERING ALGORITHMSJournal: International Journal of Civil Engineering and Technology (IJCIET) (Vol.8, No. 12)
Publication Date: 2017-12-26
Authors : Y. VIJAY BHASKAR REDDY L.S.S. REDDY S. SAI SATYA NARYANA REDDY;
Page : 763-767
Keywords : Clustering; Outliers; Core Point; Border Point;
Clustering is an unsupervised learning. It will divide clusters without assigning labels. The process of partitioning the data into groups known as clusters in such a way that the intraclass similarity is high and interclass similarity is low. This paper is proposed to give a comparative study of various density-based clustering algorithms of data mining. The following are different density-based clustering algorithms which will be reviewed in this paper: DBSCAN, OPTICS, and DENCLUE.
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