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 
AV  - QA276 .I585 2013
U1  - 519.5 23
PY  - 2017///
CY  - New York
PB  - Springer
KW  - Mathematical statistics
KW  - Mathematical models
KW  - Problems, exercises, etc
KW  - R (Computer program language)
KW  - Statistics
N1  - Includes index; TOC; 	Introduction.- Statistical Learning.- Linear Regression.- Classification.- Resampling Methods.- Linear Model Selection and Regularization.- Moving Beyond Linearity.- Tree-Based Methods.- Support Vector Machines.- Unsupervised Learning.- Index; CSE; CSE
N2  - This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering
UR  - https://www.worldcat.org/title/introduction-to-statistical-learning-with-applications-in-r/oclc/1014109834&referer=brief_results
UR  - http://lib.ewubd.edu/ebook/8930
ER  -