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Modern Multivariate Statistical Techniques : Regression, Classification, and Manifold Learning
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods.
From Data and Information Analysis to Knowledge Engineering ; Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005
The volume contains revised versions of selected papers presented during the 29th Annual Conference of the Gesellschaft für Klassifikation (GfKl), the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to papers on the traditional subjects Classification, Clustering, and Data Analysis, there are many papers on a wide range of topics with a strong relation to Computer Science. Examples are Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization. Application-oriented topics include Economics, Marketing, Banking and Finance, Medicine, Bioinformatics, Biostatistics, and Music Analysis.
COMPSTAT 2008 ; Proceedings in Computational Statistics
Presents methodological developments in Applied/Computational Statistics. This work covers a range of topics including Advances on Statistical Computing Environments, Methods for Classification and Clustering, Computation for Graphical Models and Bayes Nets, Computational Econometrics, and, Computational Statistics and Data Mining.
