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＜電子ブック＞
Data Analysis, Classification, and Related Methods / edited by Henk A.L. Kiers, Jean-Paul Rasson, Patrick J.F. Groenen, Martin Schader
(Studies in Classification, Data Analysis, and Knowledge Organization. ISSN:21983321)

版	1st ed. 2000.
出版者	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
出版年	2000
本文言語	英語
大きさ	XIV, 428 p. 38 illus : online resource
著者標目	Kiers, Henk A.L editor Rasson, Jean-Paul editor Groenen, Patrick J.F editor Schader, Martin editor SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Econometrics LCSH:Artificial intelligence -- Data processing  全ての件名で検索 FREE:Statistics FREE:Quantitative Economics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Data Science
一般注記	Cluster Analysis -- Discrimination, Regression Trees, and Data Mining -- Multivariate and Multidimensional Data Analysis -- Data Science -- Symbolic Data Analysis This volume contains a selection of papers presented at the Seven~h Confer­ ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub­ mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap­ plications and overview papers in various fields within data analysis, classifi­ cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica­ concerning tions HTTP:URL=https://doi.org/10.1007/978-3-642-59789-3

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