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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Amazon.com Price:  $45.66 (as of 05/05/2019 13:52 PST- Details)

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Description

This book describes the necessary ideas in a lot of fields such as medicine, biology, finance, and marketing in a common conceptual framework. Whilst the approach is statistical, the emphasis is on concepts fairly than mathematics. Many examples are given, with a liberal use of colour graphics. It’s a valuable resource for statisticians and any individual 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, enhance vector machines, classification trees and boosting—the first comprehensive remedy 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 could also be a chapter on methods for “wide” data (p bigger than n), including more than one testing and false discovery rates.

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