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(as of Nov 24, 2024 18:52:09 UTC – Details)
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book.
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates.
Publisher : Springer; 2nd edition (February 1, 2009)
Language : English
Hardcover : 745 pages
ISBN-10 : 0387848576
ISBN-13 : 978-0387848570
Item Weight : 2.96 pounds
Dimensions : 9.3 x 6 x 1.4 inches
Customers say
Customers find the content solid, informative, and valuable. They appreciate the excellent graphics and refined layout. Opinions are mixed on readability, with some finding it well-written and clear, while others say the notation is horrendous.
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