An Introduction to Statistical Learning

An Introduction to Statistical Learning
Subtitle: with Applications in R
Authors:
Publisher: Springer-Verlag New York Inc.
EAN: 9781461471370
ISBN: 1461471370
Categories: Probability and Statistics | Mathematical Physics | Mathematical and Statistical Software | Programming and Scripting Languages General | Artificial Intelligence |

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. 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.Two of the authors co-wrote The Ele


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