The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
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About this item
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.
ASIN: 0387848576
VSKU: DBV.0387848576.VG
Condition: Very Good
Author/Artist:Hastie, Trevor|Tibshirani, Robert|Friedman, Jerome
Binding: Hardcover
Note: Any images shown are stock photographs and product may differ from what is shown.
Condition Notes: Pages are clean with no markings. May show minor signs of wear or cosmetic defects marks, cuts, bends, or scuffs on the cover, spine, pages, or dust jacket. May have remainder marks on edges.
ASIN: 0387848576
VSKU: DBV.0387848576.VG
Condition: Very Good
Author/Artist:Hastie, Trevor|Tibshirani, Robert|Friedman, Jerome
Binding: Hardcover
Note: Any images shown are stock photographs and product may differ from what is shown.
Condition Notes: Pages are clean with no markings. May show minor signs of wear or cosmetic defects marks, cuts, bends, or scuffs on the cover, spine, pages, or dust jacket. May have remainder marks on edges.
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