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

Trevor Hastie, Robert Tibshirani, Jerome Friedman




[PDF.ag65] The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

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 | #4686 in Books |  imusti |  2016 | Original language:English | PDF # 1 |  9.25 x6.25 x1.25l,3.15 | File type: PDF | 745 pages

 | Springer

||66 of 67 people found the following review helpful.| Actually does something (huge) with the math|By John Mount|I have been using The Elements of Statistical Learning for years, so it is finally time to try and review it.

The Elements of Statistical Learning is a comprehensive mathematical treatment of machine learning from a statistical perspective. This means you get good derivations of popular methods such as sup| ||From the reviews:|"Like the first edition, the current one is a welcome edition to researchers and academicians equally…. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being t

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 (pr...

You can specify the type of files you want, for your gadget.The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)   |  Trevor Hastie, Robert Tibshirani, Jerome Friedman. A good, fresh read, highly recommended.

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