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 -