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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics) Hardcover – 2 Sep 2003

4.3 out of 5 stars 12 customer reviews

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Product details

  • Hardcover: 552 pages
  • Publisher: Springer; 1st ed. 2001. Corr. 3rd printing edition (2 Sept. 2003)
  • Language: English
  • ISBN-10: 0387952845
  • ISBN-13: 978-0387952840
  • Product Dimensions: 3.2 x 16.5 x 24.8 cm
  • Average Customer Review: 4.2 out of 5 stars 12 customer reviews
  • Amazon Bestsellers Rank: 1,545,882 in Books (See Top 100 in Books)
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Product description

About the Author

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.


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