The Elements of Statistical Learning

The Elements of Statistical Learning
Author :
Publisher : Springer Science & Business Media
Total Pages : 757
Release :
ISBN-10 : 9780387848587
ISBN-13 : 0387848584
Rating : 4/5 (584 Downloads)

Book Synopsis The Elements of Statistical Learning by : Trevor Hastie

Download or read book The Elements of Statistical Learning written by Trevor Hastie and published by Springer Science & Business Media. This book was released on 2009-08-26 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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