Items related to An Introduction to Statistical Learning: with Applications...
Synopsis
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...
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....
Review
Poullis, Computing Reviews, September, 2014)
“The book provides a good introduction to R. The code for all the statistical methods introduced in the book is carefully explained. ... the book will certainly be useful to many people (including me). I will surely use many examples, labs and datasets from this book in my own lectures.” (Pierre Alquier, Mathematical Reviews, July, 2014)
“The stated purpose of this book is to facilitate the...
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- PublisherSpringer
- Publication date2013
- ISBN 10 1461471397
- ISBN 13 9781461471394
- BindingPaperback
- LanguageEnglish
- Number of pages442
- Rating
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