Classification, Clustering, and Data Analysis
Subtitle: Recent Advances and Applications
By: edited by Krzysztof Jajuga, Andrzej Sokołowski, Hans-Hermann Bock
Contributors: Sokołowski, Andrzej; Bock, Hans-Hermann
Series: Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814; Studies in classification, data analysis, and knowledge organization
Publisher: Springer Berlin Heidelberg
Published: 2002
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 508
ISBN-13: 9783642561818
Description: This book deals with recent developments in classification and data analysis and presents new topics which are of central interest to modern statistics. In particular, these include: classification models and clustering methods, multivariate data analysis, symbolic data, neural networks and learning devices, phylogeny and bioinformatics, new software systems for classification and data analysis, as well as applications in social, economic, biological, medical and other sciences. 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.
Table of contents: title: Clustering and Discrimination: Clustering; Cluster Validation; Discrimination; title: Multivariate Data Analysis and Statistics: Multivariate Data Analysis; Statistical Methods; Symbolic Data Analysis; Consensus Trees and Phylogenetics; Regression Trees; Neural Networks and Genetic Algorithms; title: Applications.