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Author : Ram Gnanadesikan
Publisher : National Academies Press
Page : 116 pages
File Size : 53,7 Mb
Release : 1988-01-01
Category : Cluster analysis
ISBN : 8210379456XXX
Author : National Research Council,Division on Engineering and Physical Sciences,Commission on Physical Sciences, Mathematics, and Applications,Board on Mathematical Sciences,Committee on Applied and Theoretical Statistics,Classification and Clustering,Panel on Discriminant Analysis
Publisher : National Academies Press
Page : 0 pages
File Size : 55,6 Mb
Release : 1988-02-01
Category : Mathematics
ISBN : 0309090385
Author : J. Van Ryzin
Publisher : Elsevier
Page : 478 pages
File Size : 53,8 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483276618
Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.
Author : Vincent Wayne Mitchell
Publisher : Unknown
Page : 86 pages
File Size : 49,5 Mb
Release : 1993
Category : Cluster analysis
ISBN : IND:30000035541436
Author : Phipps Arabie,Geert de Soete
Publisher : World Scientific
Page : 508 pages
File Size : 43,8 Mb
Release : 1996
Category : Mathematics
ISBN : 9810212879
At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.
Author : Lang WU,Jin Qiu
Publisher : EDP Sciences
Page : 238 pages
File Size : 45,7 Mb
Release : 2021-04-27
Category : Mathematics
ISBN : 9782759826025
Multivariate analysis is a popular area in statistics and data science. This book provides a good balance between conceptual understanding, key theoretical presentation, and detailed implementation with software R for commonly used multivariate analysis models and methods in practice.
Author : Martin Schader,Wolfgang A. Gaul,Maurizio Vichi
Publisher : Springer Science & Business Media
Page : 702 pages
File Size : 46,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642189913
The volume presents new developments in data analysis and classification and gives an overview of the state of the art in these scientific fields and relevant applications. Areas that receive considerable attention in the book are clustering, discrimination, data analysis, and statistics, as well as applications in economics, biology, and medicine it provides recent technical and methodological developments and a large number of application papers demonstrating the usefulness of the newly developed techniques.
Author : Ullrich Heilemann,Claus Weihs
Publisher : Duncker & Humblot
Page : 168 pages
File Size : 54,7 Mb
Release : 2007-01-18
Category : Business & Economics
ISBN : 9783428524259
The analysis of cyclical macroeconomic phenomena is an important field of econometric research. In the recent past, research interests have de-emphasized quantitative forecasting exercises and have addressed the qualitative diagnosis of the relative stance of the economy regarding »upswing«, »recession«, or »boom« periods, i. e. the classification of the state of the economy into a limited number of discrete states. In this context the principal challenge is to reduce the multifaceted and sometimes abundant quantitative information about the business cycle to such qualitative statements in an efficient way. For more than six years this task was the focus of the project »Multivariate determination and analysis of business cycles« within the SFB 475 »Reduction of complexity in multivariate data structures«, funded by the German Research Foundation (DFG). The necessity for complexity reduction is, of course, not unique to business cycle analysis but is studied in many fields and in a number of ways. This broad interest in the reduction of problem dimensionality and in the appropriate combination of data and of theory caused the RWI Essen and the Statistical Department of the University of Dortmund in January 2002 to hold a workshop at the RWI Essen where the findings of this and similar projects were presented and discussed. The present publication collects revised versions of the papers presented at this workshop. Although the workshop took place some five years ago, these papers mark an importent juncture in the development of business cycle research.
Author : Jagdish N. Sheth,Lawrence Sherman
Publisher : Marketing Classics Press
Page : 18 pages
File Size : 50,8 Mb
Release : 2011-06-30
Category : Business & Economics
ISBN : 9781613111789
Author : Henk A.L. Kiers,Jean-Paul Rasson,Patrick J.F. Groenen,Martin Schader
Publisher : Springer Science & Business Media
Page : 428 pages
File Size : 42,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642597893
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.
Author : Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery
Publisher : Cambridge University Press
Page : 446 pages
File Size : 49,9 Mb
Release : 2019-07-25
Category : Business & Economics
ISBN : 9781108494205
Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.
Author : Simone Borra,Roberto Rocci,Maurizio Vichi,Martin Schader
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 45,5 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642594717
This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica, which was held in Rome, July 5-6, 1999. From the originally submitted papers, a careful review process led to the selection of 45 papers presented in four parts as follows: CLASSIFICATION AND MULTIDIMENSIONAL SCALING Cluster analysis Discriminant analysis Proximity structures analysis and Multidimensional Scaling Genetic algorithms and neural networks MUL TIV ARIA TE DATA ANALYSIS Factorial methods Textual data analysis Regression Models for Data Analysis Nonparametric methods SPATIAL AND TIME SERIES DATA ANALYSIS Time series analysis Spatial data analysis CASE STUDIES INTERNATIONAL FEDERATION OF CLASSIFICATION SOCIETIES The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America - CSNA; Gesellschaft fUr Klassifikation - GfKI; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - CGSIS; Societe Francophone de Classification -SFC. Now the IFCS includes also the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Society -SKAD; Associayao Portuguesa de Classificayao e Analise de Dados -CLAD; Korean Classification Society -KCS; Group-at-Large.
Author : Alfredo Rizzi,Maurizio Vichi,Hans-Hermann Bock
Publisher : Springer Science & Business Media
Page : 678 pages
File Size : 49,8 Mb
Release : 2013-03-08
Category : Mathematics
ISBN : 9783642722530
International Federation of Classification Societies The International Federation of Classification Societies (lFCS) is an agency for the dissemination of technical and scientific information concerning classification and multivariate data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) by the following Scientific Societies and Groups: - British Classification Society - BCS - Classification Society of North America - CSNA - Gesellschaft fUr Klassification - GfKI - Japanese Classification Society - JCS - Classification Group ofItalian Statistical Society - CGSIS - Societe Francophone de Classification - SFC Now the IFCS includes also the following Societies: - Dutch-Belgian Classification Society - VOC - Polish Classification Section - SKAD - Portuguese Classification Association - CLAD - Group at Large - Korean Classification Society - KCS IFCS-98, the Sixth Conference of the International Federation of Classification Societies, was held in Rome, from July 21 to 24, 1998. Five preceding conferences were held in Aachen (Germany), Charlottesville (USA), Edinburgh (UK), Paris (France), Kobe (Japan).
Author : Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock
Publisher : Springer Science & Business Media
Page : 468 pages
File Size : 47,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642561818
The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.
Author : Boris Mirkin
Publisher : Springer Science & Business Media
Page : 439 pages
File Size : 48,5 Mb
Release : 2013-12-01
Category : Mathematics
ISBN : 9781461304579
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor.
