Matrix Methods in Data Mining and Pattern Recognition

Matrix Methods in Data Mining and Pattern Recognition
Author :
Publisher : SIAM
Total Pages : 226
Release :
ISBN-10 : 9780898716269
ISBN-13 : 0898716268
Rating : 4/5 (268 Downloads)

Book Synopsis Matrix Methods in Data Mining and Pattern Recognition by : Lars Elden

Download or read book Matrix Methods in Data Mining and Pattern Recognition written by Lars Elden and published by SIAM. This book was released on 2007-07-12 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.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 problem-solving 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 GoogleÔ 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.Contents Preface; Part I: Linear Algebra Concepts and Matrix Decompositions. Chapter 1: Vectors and Matrices in Data Mining and Pattern Recognition; Chapter 2: Vectors and Matrices; Chapter 3: Linear Systems and Least Squares; Chapter 4: Orthogonality; Chapter 5: QR Decomposition; Chapter 6: Singular Value Decomposition; Chapter 7: Reduced-Rank Least Squares Models; Chapter 8: Tensor Decomposition; Chapter 9: Clustering and Nonnegative Matrix Factorization; Part II: Data Mining Applications. Chapter 10: Classification of Handwritten Digits; Chapter 11: Text Mining; Chapter 12: Page Ranking for a Web Search Engine; Chapter 13: Automatic Key Word and Key Sentence Extraction; Chapter 14: Face Recognition Using Tensor SVD. Part III: Computing the Matrix Decompositions. Chapter 15: Computing Eigenvalues and Singular Values; Bibliography; Index.


Matrix Methods in Data Mining and Pattern Recognition Related Books

Matrix Methods in Data Mining and Pattern Recognition
Language: en
Pages: 226
Authors: Lars Elden
Categories: Computers
Type: BOOK - Published: 2007-07-12 - Publisher: SIAM

GET EBOOK

Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented b
Matrix Methods in Data Mining and Pattern Recognition
Language: en
Pages: 234
Authors: Lars Elden
Categories: Computers
Type: BOOK - Published: 2007-01-01 - Publisher: SIAM

GET EBOOK

This application-oriented book describes how modern matrix methods can be used to solve problems in data mining and pattern recognition, gives an introduction t
Matrix Methods in Data Mining and Pattern Recognition, Second Edition
Language: en
Pages: 244
Authors: Lars Elden
Categories: Mathematics
Type: BOOK - Published: 2019-08-30 - Publisher: SIAM

GET EBOOK

This thoroughly revised second edition provides an updated treatment of numerical linear algebra techniques for solving problems in data mining and pattern reco
Understanding Complex Datasets
Language: en
Pages: 268
Authors: David Skillicorn
Categories: Computers
Type: BOOK - Published: 2007-05-17 - Publisher: CRC Press

GET EBOOK

Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most
Introduction to Matrix Analytic Methods in Stochastic Modeling
Language: en
Pages: 331
Authors: G. Latouche
Categories: Mathematics
Type: BOOK - Published: 1999-01-01 - Publisher: SIAM

GET EBOOK

Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.