Principles of Data Mining

Hand, David J.

ISBN 10: 026208290X / ISBN 13: 9780262082907

Editore: The MIT Press, 2001

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This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1250grams, ISBN:9780262082907.

Codice articolo 5580680

Dati bibliografici

• Titolo: Principles of Data Mining
• Editore: The MIT Press
• Data di pubblicazione: 2001
• Lingua: Inglese
• ISBN 10: 026208290X
• ISBN 13: 9780262082907
• Rilegatura: Rilegato
• Condizione: Good
• Peso: 1250 grammi
• Cataloghi dei venditori:
  • Science & Technology

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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