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An Introduction to Statistical Learning: with Applications in R

An Introduction  to Statistical  Learning: with Applications in R
Author: James, D. Witten, T. Hastie, R. Tibshirani
Url: https://web.stanford.edu/~hastie/local.ftp/Springer/ISLR_print1.pdf
Format: Pdf
Year: 2013
Category: Statistical Learning Theory
Pages: 441
Clicks: 973

One of the first books in this area— The Elements of Statistical Learning (ESL) (Hastie, Tibshirani, and Friedman)—was published in 2001, with a second edition in 2009. ESL has become a popular text not only in statis- tics but also in related fields. One of the reasons for ESL’s popularity is its relatively accessible style. But ESL is intended for individuals with ad- vanced training in the mathematical sciences. An Introduction to Statistical Learning (ISL) arose from the perceived need for a broader and less tech- nical treatment of these topics. In this new book, we cover many of the same topics as ESL, but we concentrate more on the applications of the methods and less on the mathematical details. We have created labs illus- trating how to implement each of the statistical learning methods using the popular statistical software package R. These labs provide the reader with valuable hands-on experience.

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