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Survey Paper on Quality Cluster Generation Using Random Projections

P.A. Gat, K.S.Kadam,

Affiliations
Department of Computer Science, D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji, India
:10.22362/ijcert/2018/v5/i12/v5i1203


Abstract
Clustering is the grouping of a particular set of objects based on their characteristics, aggregating them according to their similarities. Regarding data mining, this methodology partitions the data implementing a specific join algorithm, most suitable for the desired information analysis. Clusters will obtained by using density-based clustering and DBSCAN clustering. DBSCAN cluster is a fast clustering technique, large complexity and requires more parameters. To overcome these problems uses the OPTICS Density-based algorithm. The algorithm requires single factor, namely the least amount of points in a cluster which can necessary as input in density- based technique. Using random projection improving the cluster quality and runtime.


Citation
. International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.5, Issue 12, December - 2018,


Keywords : Cluster Analysis, Random Projections, Neighbouring.

References
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DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i12/v5i1203

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DOI:10.22362/ijcert


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