Eldén ,Lars  <br/><br/>
Matrix methods in data mining and pattern recognition 

 - Philadelphia:  Society for Industrial and Applied Mathematics,  2007. 
 - 224 p.;  ill.;  25 cm.; 
<br/><br/>Includes bibliographical references  and index. 
<br/><br/> 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." "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 
<br/><br/><label>ISBN: </label>9780898716269 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Algebras, Linear	<br/>Data mining<br/>Pattern recognition systems<br/>Mathematical models<br/>Pattern recognition systems
<br/><br/><label>Dewey Class. No.: </label>005.74  / ELD