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Issue No.06 - Nov.-Dec. (2012 vol.9)
pp: 1850-1852
R. J. G. B. Campello , Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
D. Moulavi , Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
J. Sander , Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
ABSTRACT
In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a userdefined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity.
INDEX TERMS
Clustering algorithms, Complexity theory, Data mining, Data visualization, Bioinformatics,AUTO-HDS, Data mining, clustering, bioinformatics databases
CITATION
R. J. G. B. Campello, D. Moulavi, J. Sander, "A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no. 6, pp. 1850-1852, Nov.-Dec. 2012, doi:10.1109/TCBB.2012.115
REFERENCES
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[7] M. Ankerst, M.M. Breunig, H.-P. Kriegel, and J. Sander, “Optics: Ordering Points to Identify the Clustering Structure,” SIGMOD Record, vol. 28, pp. 49-60, June 1999.
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[10] W. Stuetzle and R. Nugent, “A Generalized Single Linkage Method for Estimating the Cluster Tree of a Density,” J. Computational and Graphical Statistics, vol. 19, no. 2, pp. 397-418, 2010.
[11] J. Sander, X. Qin, Z. Lu, N. Niu, and A. Kovarsky, “Automatic Extraction Of Clusters from Hierarchical Clustering Representations,” Proc. Pacific-Asia Conf. Advances in Knowledge Discovery and Data Mining, pp. 75-87, 2003.
[12] L. Lelis and J. Sander, “Semi-Supervised Density-Based Clustering,” Proc. IEEE Ninth Int'l Conf. Data Mining (ICDM), pp. 842 -847, 2009.
[13] A.K. Jain and R.C. Dubes, Algorithms for Clustering Data. Prentice Hall, 1988.
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