Matrix Methods in Data Mining and Pattern Recognition

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    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 II, linear algebra techniques are applied to data mining problems. Part III 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.

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    Number of Pages: 184
    Format(s): Paperback - ISBN: 9780898716269
    Publication Date:
    Listed in: Data mining, Pattern recognition
    Publisher: Society for Industrial & Applied Mathematics,U.S.

    Books by Lars Elden

    Paperback

    RRP: £49.00

    Sale Price: £31.86

    Save: £17.14 per copy!

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