Classification and Related Methods of Data Analysis
Conference Proceedings
Published in April 1988
Book
Hardback
766 pages
978-0-444-70404-7 (ISBN)
Description
A range of topics and perspectives in classification, clustering, statistics and data analysis are brought together in this volume, including surveys, new methods for clustering objects, and procedures for analysing multivariate or relational data. Emphasized are probabilistic models, pattern recognition and image analysis, the analysis of strains and molecules, algebraic methods from lattice and consensus theory, correspondence and canonical analysis, and the interference between classification and retrieval or expert systems.
A range of topics and perspectives in classification, clustering, statistics and data analysis are brought together in this volume, including surveys, new methods for clustering objects, and procedures for analysing multivariate or relational data. Emphasized are probabilistic models, pattern recognition and image analysis, the analysis of strains and molecules, algebraic methods from lattice and consensus theory, correspondence and canonical analysis, and the interference between classification and retrieval or expert systems.
A range of topics and perspectives in classification, clustering, statistics and data analysis are brought together in this volume, including surveys, new methods for clustering objects, and procedures for analysing multivariate or relational data. Emphasized are probabilistic models, pattern recognition and image analysis, the analysis of strains and molecules, algebraic methods from lattice and consensus theory, correspondence and canonical analysis, and the interference between classification and retrieval or expert systems.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 230 mm
Width: 150 mm
ISBN-13
978-0-444-70404-7 (9780444704047)
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Schweitzer Classification
Content
Survey Lectures. Clustering and Classification Methods. Probabilistic Methods in Cluster Analysis. Pattern Recognition and Discrimination Methods. Consensus and Aggregation Methods. Biological Taxonomy, Phylogenies, and Sequence Analysis. Similarity Representation, Scaling Methods, and Valuations. Linear Data Analysis and Extensions.lgebraic Methods of Data Analysis. Special Topics from Data Analysis and Statistics. Classification and Data Bases, Expert Systems, Information Retrieval, and Computational Aspects. Invited Papers (by: J.C. Gower; R.D. Luce; F. Murtagh; H. Niemann; R.R. Sokal; E.N. Trifonov; F. Critchley; I.C. Lerman; G. De Soete; M.P. Windham; L.C.A. Corsten; P.A. Devijver, M.M. Dekesel; J.A. Hartigan; T. Saito; K.-D. Wernecke, G. Kalb, E. Sturzebecher; J.P. Barthelemy, B. Monjardet; W.H.E. Day; D.P. Faith; B. Leclerc; M.D. Hendy et al.; D. Sankoff et al.; J.D. Carroll, W.S. DeSarbo, G. De Soete; B. Fichet; K.R. Gabriel, C.L. Odoroff, S. Choi; W.J. Heiser; L. Hubert, P. Arabie; Y. Escoufier; A. Rizzi; C.J.F. Ter Braak; B. Ganter; M. Nagel, H.-J. Dobberkau; E. Backer; F. Gebhardt).