An Introduction To Statistical Learning With Applications In R by Trevor Hastie and Gareth James and Robert Tibshirani and Daniela Witten

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.

Publisher:	Springer
Year:	2015
Binding:	Hardback
ISBN:	9781461471370
Condition:	Near Mint
Description:	No DJ As Issued; Heavy.

Note: This image is from a stock photo and may differ from the actual cover.

SKU: 1598341
Location: Math