Item description for Classification, Clustering and Data Analysis by K. Jajuga, Andrzej Sokoowski & Hans Hermann Bock...
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.
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Est. Packaging Dimensions: Length: 1" Width: 6" Height: 9" Weight: 1.7 lbs.
Release Date Aug 15, 2002
ISBN 354043691X ISBN13 9783540436911
Availability 102 units. Availability accurate as of Feb 26, 2017 11:52.
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More About K. Jajuga, Andrzej Sokoowski & Hans Hermann Bock
Reviews - What do customers think about Classification, Clustering and Data Analysis?
Understand clusters and clustering deeply Aug 18, 2006
This is a good and broad approach about cluster and clustering. It is better for those who want to understand deeply the theme. Is has lot of formulas and mathmatics.
different methods for finding clusters Jan 12, 2005
The book has a nice treatment of the problem of finding, in some sense, clusters in data. Several papers point out that there is often some subjectivity here, as to which data sits in a particular cluster. Fuzziness in the boundary of a cluster. It can depend on what your underlying model is.
Possibly of interest to some is work on high dimensionality data, and trying to find clusters in these. Even visualisations might be non-trivial.
The book has value in letting you see a variety of ideas for finding clusters. Perhaps some of these might prove germane to your research.