The Elements of Statistical Learning | Hastie | 0387848576

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The book explains the major 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. Several cases are given, with a liberal use of colour graphics. It is a important resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is wide, from supervised learning (prediction) to unsupervised learning. The many topics incorporate neural networks, support vector machines, classification trees and boosting---the first comprehensive approach of this topic in any book. This significant new edition highlights 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.
  • ISBN-13: 9780387848570
  • ISBN-10: 0387848576
  • Language- English
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