Shows how modern matrix methods can be applied in data mining and pattern recognition.
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Lars Eldén is professor of numerical analysis at Linköping University in Sweden. He was head of the Mathematics Department at Linköping University from 1997 to 2001 and Director of the National Supercomputer Centre, Linköping, from 1990 to 1991. He is the author, along with L. Wittmeyer-Koch and H. Bruun Nielsen, of Introduction to Numerical Computation: Analysis and MATLAB Illustrations (Studentlitteratur AB, 2004).
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Paperback. Zustand: Good. Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part I, linear algebra techniques are applied to data mining problems. Part I is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book. Bestandsnummer des Verkäufers CIN0898716268G
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