Introduction to Data Mining - Rilegato

Tan, Pang-Ning; Steinbach, Michael; Kumar, Vipin

Rilegato

ISBN 10: 0321321367 ISBN 13: 9780321321367

Casa editrice: Pearson College Div, 2005

Riassunto

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.

Su questo libro

Product Description:

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. Material from related fields such as statistics and linear algebra, is integrated directly into the text. 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. Theoretical and practical coverage of all data mining topics Large number of integrated examples and figures Instructor Resources including solutions for most exercises and complete set of lecture slides (PowerPoint format). Minimal prerequisites-assume only a modest statistics or mathematics background, and no database knowledge is needed Predictive modeling Association analysis Clustering Anomaly detection Visualization

Su questa edizione

• Editore: Pearson College Div
• Data di pubblicazione: 2005
• ISBN 10: 0321321367
• ISBN 13: 9780321321367
• Rilegatura: Copertina rigida
• Numero di pagine: 769