The Elements of Statistical Learning

The Elements of Statistical Learning : Data Mining, Inference, and Prediction

4.35 (873 ratings by Goodreads)
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This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized more

Product details

  • Electronic book text
  • Springer-Verlag New York Inc.
  • United States
  • 2nd Revised edition
  • 0387848584
  • 9780387848587

Review quote

JOURNAL OF CLASSIFICATION, JUNE 2004"This is a great book. All three authors have track records for clear exposition and are famously gifted for finding intuitive explanations that illuminate technical results In particular, we admire the book for its: -outstanding use of real data examples to motivate problems and methods;-unified treatment of flexible inferential procedures in terms of maximization of an objective function subject to a complexity penalty;-lucid explanation of the amazing performance of the AdaBoost algorithm in improving classification accuracy for almost any rule;-clear account of support vector machines in terms of traditional statistical paradigms; -regular introduction of some new insight, such as describing self-organizing maps as constrained k-means clustering. No modern statistician or computer scientist should be without this book." JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, JUNE 2004"In the words of the authors, the goashow more

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873 ratings
4.35 out of 5 stars
5 55% (480)
4 30% (262)
3 11% (99)
2 3% (26)
1 1% (6)
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