Principles of Data Mining (Adaptive Computation and Machine Learning) - Hardcover

Hand, David J.; Mannila, Heikki; Smyth, Padhraic

Hardcover

ISBN 10: 026208290X ISBN 13: 9780262082907

Publisher: Bradford Books, 2001

Synopsis

The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.

The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

About this title

About the Author:

David Hand is Professor of Statistics, Department of Mathematics, Imperial College, London.

About this edition

• Publisher: Bradford Books
• Publication date: 2001
• ISBN 10: 026208290X
• ISBN 13: 9780262082907
• Binding: Hardcover
• Edition number: 1
• Number of pages: 546