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E-book
Author James, Gareth (Gareth Michael), author.

Title An introduction to statistical learning : with applications in R / Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Published New York, NY : Springer, [2013]
©2013

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Description 1 online resource
Series Springer texts in statistics, 1431-875X ; 103
Springer texts in statistics ; 103.
Contents Introduction -- Statistical Learning -- Linear Regression -- Classification -- Resampling Methods -- Linear Model Selection and Regularization -- Moving Beyond Linearity -- Tree-Based Methods -- Support Vector Machines -- Unsupervised Learning
Summary 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. 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
Analysis Statistics
Mathematical statistics
Statistical Theory and Methods
Statistics and Computing/Statistics Programs
Theoretical, Mathematical and Computational Physics
Notes Includes index
English
Online resource; title from PDF title page (SpringerLink, viewed July 9, 2013)
Subject Mathematical statistics.
R (Computer program language)
Statistics.
Statistics as Topic
statistics.
Estadística matemática
R (Lenguaje de programación)
Estadística
Mathematical statistics
R (Computer program language)
Statistik
Maschinelles Lernen
Statistiek.
Programmeertalen.
Statistique mathématique.
Modèles mathématiques.
Statistique mathématique -- Problèmes et exercices.
Modèles mathématiques -- Problèmes et exercices.
Genre/Form Statistics
Problems and exercises
Elektronische boeken.
Statistics.
Statistiques.
Form Electronic book
Author Witten, Daniela, author.
Hastie, Trevor, author.
Tibshirani, Robert, author.
ISBN 9781461471387
1461471389
1461471370
9781461471370