
2007 / x + 224 pages / Softcover / ISBN: 9780898716269 / List Price $78.50 / SIAM Member Price $54.95 / Order Code FA04
Table of Contents
Preface
Index
Sample Chapter
Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This applicationoriented 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.
Matrix Methods in Data Mining and Pattern Recognition is divided into three parts. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problemsolving environments such as MATLAB®. Some mathematical proofs that emphasize the existence and properties of the matrix decompositions are included. 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 by the author are 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.
Audience
The book is intended for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.
About the Author
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. WittmeyerKoch and H. Bruun Nielsen, of Introduction to Numerical Computation: Analysis and MATLAB Illustrations (Studentlitteratur AB, 2004).
Read the review of this book that appeared in SIAM Review.
ISBN: 9780898716269