03029cam a22003977a 4500
28311
28311
62947
2013936251
9781461471370
1461471370 (acid-free paper)
BTCTA
QA
lcco
519.5
James, Gareth
36078
An introduction to statistical learning :
with applications in R
Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Statistical learning
New York :
Springer,
c2013.
©2013
xiv, 426 p. :
ill. (some col.) ;
24 cm.
Springer texts in statistics,
1431-875X ;
103
Includes index.
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.</p> <p>Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
CSCI323
Mathematical statistics
834
Mathematical models
35121
Mathematical statistics
Problems, exercises, etc.
13228
Mathematical models
Problems, exercises, etc.
36079
R (Computer program language)
2458
Statistics
2068
Witten, Daniela
36080
Hastie, Trevor
36081
Tibshirani, Robert
36082
Springer texts in statistics
36083
https://static1.squarespace.com/static/5ff2adbe3fe4fe33db902812/t/6062a083acbfe82c7195b27d/1617076404560/ISLR%2BSeventh%2BPrinting.pdf
eBook
https://uowd.box.com/s/w3nr0q6amitab7ji3655n4lf5ia4tlic
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