Acknowledged author wrote Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) comprising 184 pages back in 2007. Textbook and etextbook are published under ISBN 0898716268 and 9780898716269. Since then Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) textbook was available to sell back to BooksRun online for the top buyback price of $17.25 or rent at the marketplace.
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.