By J. A. Hartigan (auth.), Professor Dr. Henk A. L. Kiers, Professor Dr. Jean-Paul Rasson, Dr. Patrick J. F. Groenen, Professor Dr. Martin Schader (eds.)

ISBN-10: 3540675213

ISBN-13: 9783540675211

ISBN-10: 3642597890

ISBN-13: 9783642597893

This quantity features a choice of papers awarded on the Seven~h Confer­ ence of the overseas Federation of class Societies (IFCS-2000), which was once held in Namur, Belgium, July 11-14,2000. From the initially sub­ mitted papers, a cautious evaluate approach regarding reviewers in keeping with paper, ended in the choice of sixty five papers that have been thought of appropriate for booklet during this publication. the current publication comprises unique study contributions, leading edge ap­ plications and evaluation papers in a number of fields inside of information research, classifi­ cation, and similar tools. Given the quick e-book procedure, the learn effects are nonetheless updated and coincide with their genuine presentation on the IFCS-2000 convention. the themes captured are: • Cluster research • comparability of clusterings • Fuzzy clustering • Discriminant research • combination versions • research of relationships facts • Symbolic info research • Regression bushes • facts mining and neural networks • trend popularity • Multivariate facts research • strong facts research • information technology and sampling The IFCS (International Federation of category Societies) The IFCS promotes the dissemination of technical and clinical details facts research, type, similar equipment, and their applica­ referring to tions.

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Sec. -! of Ciok pt al. (1998)). • Double grade clustering (DGC) is based dir('ctl~' Oll optimal permutations prm'ided by GCA. aggrTi. v,'here aggrX denotes aggregated X: in each casp we aggregate IUZ7lu:ent categories according to the GCA permutations. • Optimal grade clustering (OGC) maximizes fI* (aggr X. IIggrl'). In this case, the clusters lIlay not consist of categories adjacellt according to the GCA arrangements. These arrangements serw just i\S good starting points for the optimalization procedure.

1975): Clustering Algorithms. John Wiley & Sons, New York. N. (1967): A General Theory of Classificatory Sorting Strategies I, Hierarchical Systems. Computer Journal, g, 373-380. Unsupervised N on-hierarchical Entropy-based Clustering M. Jardino Laboratoire d'Informatique pour la l\1ecanique et les Sciences de rIugenieur. BP 133 - F91403 ORSAY Cedex(France), (e-mail: jardino@limsi,fr) Abstract. \lVe present an unsupervised non-hierarchical clustering which realizes a partition of unlabelled objects in K non-overlapping dusters.

Special attention will be paid to the interpretation aspects versus the formal inference based on clustering qualit~, measures. The discussed example shows that formally similar solutions may differ significantly from the interpretation point of dew. 1 Double grade clustering and optimal grade clustering Grade correspondence analysis and univariate and bivariate clustering lllcthods based on it were presented during the IFCS '98 conferenc(' (Ciok (1998). Here we recall only a few general ideas underlying these methods.

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Data Analysis, Classification, and Related Methods by J. A. Hartigan (auth.), Professor Dr. Henk A. L. Kiers, Professor Dr. Jean-Paul Rasson, Dr. Patrick J. F. Groenen, Professor Dr. Martin Schader (eds.)

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