A grid clustering algorithm using cluster boundaries

Author

Edla, D.R. ; Jana, Prasanta K.

Author_Institution

Dept. of Comput. Sci. & Eng., Indian Sch. of Mines, Dhanbad, India

fYear

2012

fDate

Oct. 30 2012-Nov. 2 2012

Firstpage

254

Lastpage

259

Abstract

Grid-based clustering methods have been extensively applied on large data sets because of low computational cost. In this paper, we propose a new algorithm for grid-based clustering by finding the optimal grid-size using the boundaries of the clusters. The algorithm has linear time complexity. The problem of outliers is resolved with the help of local outlier factor (LOF). We apply the proposed method on various synthetic as well as biological data sets. The results are compared with K-means and few existing grid-based techniques. The comparison results show the effectiveness of the proposed method.

Keywords

computational complexity; data mining; pattern classification; pattern clustering; LOF; biological data sets; cluster boundary; grid clustering algorithm; k-means techniques; linear time complexity; local outlier factor; optimal grid-size; synthetic data sets; Algorithm design and analysis; Biology; Clustering algorithms; Clustering methods; Partitioning algorithms; Shape; Spatial databases; Clustering; biological data; grid; local outlier factor; normalized information gain; outlier;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2012 World Congress on

Conference_Location

Trivandrum

Print_ISBN

978-1-4673-4806-5

Type

conf

DOI

10.1109/WICT.2012.6409084

Filename

6409084