Introduction to Data Mining Tan, Pang-Ning; Steinbach, Michael and Kumar, Vipin

Introduction to Data Mining Tan, Pang-Ning; Steinbach, Michael and Kumar, Vipin

ISBN 10: 0321321367 / ISBN 13: 9780321321367

Edité par Pearson, 2005

A propos de cet article

N° de réf. du vendeur QCAK--0032

Détails bibliographiques

• Titre: Introduction to Data Mining Tan, Pang-Ning; Steinbach, Michael and Kumar, Vipin
• Éditeur: Pearson
• Date de parution: 2005
• Langue: anglais
• ISBN à 10 chiffres: 0321321367
• ISBN à 13 chiffres: 9780321321367
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

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.

Présentation de l'éditeur

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