This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter ...
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This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.
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Add this copy of An Introduction to Statistical Learning to cart. $19.34, very good condition, Sold by Bookmonger.Ltd rated 5.0 out of 5 stars, ships from Hillside, NJ, UNITED STATES, published 2017 by Createspace Independent Pub.
Add this copy of An Introduction to Statistical Learning to cart. $77.46, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Newport Coast, CA, UNITED STATES, published 2017 by Createspace Independent Pub.
Add this copy of An Introduction to Statistical Learning to cart. $114.56, new condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Newport Coast, CA, UNITED STATES, published 2017 by Createspace Independent Pub.
