Introduction to Data Mining, First Edition, Pearson New International Edition de Pang-Ning Tan; Michael Steinbach; Vipin Kumar: Fine Trade Paperback (2014) 1st Edition

Descripci�n

Pearson Education, 2014. Trade Paperback. Fine. Interior pristine. Spine straight, tight and uncreased. Light corner wear. Not from a library. No remainder mark. 732 pages. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

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Detalles bibliogr�ficos

T�tulo: Introduction to Data Mining, First Edition, Pearson New International Edition
Editor: Pearson Education, Harlow, Essex, England
Fecha de publicaci�n: 2014
Idioma: Ingl�s
ISBN 10: 1292026154
ISBN 13: 9781292026152
Encuadernaci�n: Trade Paperback
Edici�n: 1st Edition
Estado: Fine

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Sinopsis

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Quotes This book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts. -Sanjay Ranka, University of Florida In my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules). -Mohammed Zaki, Rensselaer Polytechnic Institute

Rese�a del editor

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Quotes This book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts. -Sanjay Ranka, University of Florida In my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules). -Mohammed Zaki, Rensselaer Polytechnic Institute

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