TY  - BOOK
AU  - James,Gareth
AU  - Witten,Daniela
AU  - Hastie,Trevor
AU  - Tibshirani,Robert
TI  - An introduction to statistical learning: with applications in R 
T2  - Springer texts in statistics,
SN  - 9781461471370
U1  - 519.5 
PY  - 2013///
CY  - New York
PB  - Springer
KW  - Mathematical statistics
KW  - Statistics
N1  - Includes index; Ch. 1 Introduction -- 
Ch. 2 Statistical learning -- 
Ch. 3 Linear regression -- 
Ch. 4 Classification -- 
Ch. 5 Resampling methods -- 
Ch. 6 Linear model selection and regularization -- 
Ch. 7 Moving beyond linearity -- 
Ch. 8 Tree-based methods -- 
Ch. 9 Support vector machines -- 
Ch. 10 Unsupervised learning
N2  - 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
ER  -