An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

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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.

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An Introduction To Statistical Learning


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Author by : Gareth James
Languange Used : en
Release Date : 2013-06-24
Publisher by : Springer Science & Business Media

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning,

The Elements Of Statistical Learning


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Author by : Trevor Hastie
Languange Used : en
Release Date : 2001-01-01
Publisher by : Springer Science & Business Media

This book describes the important ideas in a common conceptual framework. While the approach is statistical, t

Machine Learning And Data Mining In Pattern Recognition


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Author by : Petra Perner
Languange Used : en
Release Date : 2016-06-27
Publisher by : Springer

This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Da

Statistical Regression And Classification


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Author by : Norman Matloff
Languange Used : en
Release Date : 2017-09-19
Publisher by : CRC Press

Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at

Big Data Analytics With R


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Author by : Simon Walkowiak
Languange Used : en
Release Date : 2016-07-29
Publisher by : Packt Publishing Ltd

Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Da

Multimedia Communications Services And Security


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Author by : Andrzej Dziech
Languange Used : en
Release Date : 2017-11-27
Publisher by : Springer

This volume constitutes the refereed proceedings of the 9th International Conference on Multimedia Communicati

Probability And Statistics With R Second Edition


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Author by : Maria Dolores Ugarte
Languange Used : en
Release Date : 2015-07-21
Publisher by : CRC Press

Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first ed

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