An approach to cluster separability in a partition

Information Sciences - Tập 305 - Trang 208-218 - 2015
K. Sabo1, R. Scitovski1
1Department of Mathematics, University of Osijek, Trg Ljudevita Gaja 6, HR-31000 Osijek, Croatia

Tài liệu tham khảo

Aurenhammer, 2000, Voronoi diagrams, 201 Bandyopadhyay, 2013 Bezdek, 2005 A. Ben-Hur, A. Elisseeff, I. Guyon, A stability based method for discovering structure in clustered data, in: Pacific Symposium on Biocomputing, Lihue, Hawaii, USA, 2002, pp. 6–17. Bertrand, 2006, Loevinger’s measures of rule quality for assessing cluster stability, Comput. Stat. Data Anal., 50, 992, 10.1016/j.csda.2004.10.012 B. Durak, A Classification Algorithm Using Mahalanobis Distances Clustering of Data with Applications on Biomedical Data Set, Ph.D. Thesis, The Graduate School of Natural and Applied Sciences of Middle East Technical University, 2011. Gan, 2007 Hennig, 2007, Cluster-wise assessment of cluster stability, Comput. Stat. Data Anal., 52, 258, 10.1016/j.csda.2006.11.025 Iyigun, 2010, A generalized Weiszfeld method for the multi-facility location problem, Oper. Res. Lett., 38, 207, 10.1016/j.orl.2009.11.005 Kogan, 2007 Lange, 2004, Stability-based validation of clustering solutions, Neural Comput., 16, 1299, 10.1162/089976604773717621 Leisch, 2006, A toolbox for k-centroids cluster analysis, Comput. Stat. Data Anal., 51, 526, 10.1016/j.csda.2005.10.006 von Luxburg, 2009, Clustering stability: an overview, Found. Trends Mach. Learn., 2, 235 Okabe, 2000 Pascual, 2010, Cluster stability assessment based on theoretic information measures, Pattern Recognit. Lett., 31, 454, 10.1016/j.patrec.2009.07.009 D. Reem, The geometric stability of Voronoi diagrams with respect to small changes of the sites, in: Proceedings of the 27th Annual ACM Symposium on Computational Geometry (SoCG 2011), 2011, pp. 254–263. D. Reem, The Geometric Stability of Voronoi Diagrams in Normed Spaces which are not Uniformly Convex, 2012, 1212.1094 [cs.CG]. Sabo, 2014, Center-based l1-clustering method, Int. J. Appl. Math. Comput. Sci., 24, 151, 10.2478/amcs-2014-0012 Sabo, 2013, One-dimensional center-based l1-clustering method, Optim. Lett., 7, 5, 10.1007/s11590-011-0389-9 Sabo, 2012, Uniform distribution of the number of voters per constituency on the basis of a mathematical model, Hrvatska i komparativna javna uprava, 14, 229 Scitovski, 2014, Analysis of the k-means algorithm in the case of data points occurring on the border of two or more clusters, Knowl.-Based Syst., 57, 1, 10.1016/j.knosys.2013.11.010 Scitovski, 2013, A fast partitioning algorithm and its application to earthquake investigation, Comput. Geosci., 59, 124, 10.1016/j.cageo.2013.06.010 Shamir, 2010, Model selection and stability in k-means clustering, Mach. Learn., 80, 213, 10.1007/s10994-010-5177-8 Späth, 1983 Steinley, 2007, Initializing k-means batch clustering: a critical evaluation of several techniques, J. Classif., 24, 99, 10.1007/s00357-007-0003-0 Su, 2010, Constrained clustering with k-means type algorithms, 81 Teboulle, 2007, A unified continuous optimization framework for center-based clustering methods, J. Mach. Learn. Res., 8, 65 Theodoridis, 2009 Volkovich, 2007, Building initial partitions through sampling techniques, Eur. J. Oper. Res., 183, 1097, 10.1016/j.ejor.2005.12.045