The Elements of Statistical Learning

Name: The Elements of Statistical Learning
Brand: Springer-Verlag New York Inc.
SKU: 9780387848570-G
Price: 50.79 EUR
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By Trevor Hastie

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Description

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.

Product details

Edition:: 2
Languages:: Original: English
Number of Pages:: 745
Age Recommendation:: 10 – 80 years
Publisher:: Springer-Verlag New York Inc.
Publication Date:: 2009-02-09
ISBN / EAN:: 9780387848570
Weight:: 1200 g
Dimensions:: 16/24/4 cm
GPSR Manufacturer Reference:: [email protected]

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The items bear minimal signs of past use, such as light scratches or memories in the form of markings. These signs of wear give the items a charming character and tell stories of their previous owners, while not affecting their functionality.

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