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An Introduction to Statistical Learning

An Introduction to Statistical Learning


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About the Book


About the Author:

Gareth James is a professor of data sciences and operations at the University of Southern California. He has published an extensive body of methodological work in the domain of statistical learning with particular emphasis on high-dimensional and functional data. The conceptual framework for this book grew out of his MBA elective courses in this area.

Daniela Witten is an associate professor of statistics and biostatistics at the University of Washington. Her research focuses largely on statistical machine learning in the high-dimensional setting, with an emphasis on unsupervised learning.


Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University, and are co-authors of the successful textbook Elements of Statistical Learning. 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.


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Product Details
  • ISBN-13: 9781461471370
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Depth: 22
  • Height: 239 mm
  • No of Pages: 426
  • Series Title: Springer Texts in Statistics
  • Sub Title: With Applications in R
  • Width: 196 mm
  • ISBN-10: 1461471370
  • Publisher Date: 01 Sep 2017
  • Binding: Hardback
  • Edition: 1st ed. 2013, Corr. 7th printing 2017
  • Language: English
  • Returnable: Y
  • Spine Width: 25 mm
  • Weight: 956 gr


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