http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Classification, Clustering, and Data Analysis
1 online resource (xi, 508 pages 84 illustrations)
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.
Clustering and Discrimination: Clustering; Cluster Validation; Discrimination -- Multivariate Data Analysis and Statistics: Multivariate Data Analysis; Statistical Methods; Symbolic Data Analysis; Consensus Trees and Phylogenetics; Regression Trees; Neural Networks and Genetic Algorithms -- Applications.
edited by Krzysztof Jajuga, Andrzej Sokołowski, Hans-Hermann Bock.
Studies in classification, data analysis, and knowledge organization