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An Introduction to Statistical Learning

with Applications in R

Gebonden Engels 2014 9781461471370
Verwachte levertijd ongeveer 8 werkdagen

Samenvatting

'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.

Specificaties

ISBN13:9781461471370
Trefwoorden:statistiek, R
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:426
Druk:1
Verschijningsdatum:11-7-2014

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Over Gareth James

Gareth R. James, Gareth Robert James (CCIA, CCEA, MCSE:Security, MCT, VMware VCP, Checkpoint CCSE, RSA CSE, Security+) is an IT consultant focusing on virtualization architecture. He has worked as Citrix Consultant for Citrix Gold and Platinum Partners. He has focused on supporting Microsoft architecture and security, including PKI and firewalls. He has also worked as a Microsoft and Citrix trainer. Gareth holds an honors degree in Electronic Engineering from the University of Natal-Durban.

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Inhoudsopgave

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.

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        An Introduction to Statistical Learning