عنوان

An introduction to statistical learning :

(Number (ISBN

1461471370

(Number (ISBN

1461471389

(Number (ISBN

9781461471370

(Number (ISBN

9781461471387

Erroneous ISBN

9781461471370

Number

b623696

Title Proper

An introduction to statistical learning :

General Material Designation

[Book]

Other Title Information

with applications in R /

First Statement of Responsibility

Gareth James [and others].

Specific Material Designation and Extent of Item

1 online resource

Series Title

Springer texts in statistics,

Volume Designation

103

ISSN of Series

1431-875X ;

Text of Note

Includes index.

Text of Note

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.

Source for Acquisition/Subscription Address

Springer

International Standard Book Number

9781461471370

Mathematical statistics.

R (Computer program language)

Statistics as Topic.

Maschinelles Lernen

Mathematical statistics.

Programmeertalen.

R (Computer program language)

Statistiek.

Statistik

MAT029000

PBT

PBT

Number

Edition

Class number

Book number

Class number

James, Gareth, (Gareth Michael)

Date of Transaction

20201221082812.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

270410

Y