عنوان

An introduction to statistical learning :

شابک

1461471370

شابک

9781461471370

شابک اشتباه

1461471389

شابک اشتباه

9781461471387

شماره

b623697

عنوان اصلي

An introduction to statistical learning :

نام عام مواد

[Book]

ساير اطلاعات عنواني

with applications in R /

نام نخستين پديدآور

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani.

وضعيت ويراست

[Uncorrected edition].

نام خاص و کميت اثر

xiv, 426 pages :

ساير جزييات

illustrations (some color) ;

ابعاد

24 cm.

عنوان فروست

Springer texts in statistics,

مشخصه جلد

103

شاپا ي ISSN فروست

1431-875X ;

متن يادداشت

Includes index.

متن يادداشت

Introduction -- Statistical learning -- Linear regression -- Classification -- Resampling methods -- Linear model selection and regularization -- Moving beyond linearity -- Tree-based methods -- Support vector machines -- Unsupervised learning.

بدون عنوان

0

متن يادداشت

"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. Provides tools for Statistical Learning that are essential for practitioners in science, industry and other fields. Analyses and methods are presented in R. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering. Extensive use of color graphics assist the reader"--Publisher description.

عنوان اصلي به زبان ديگر

Statistical learning

موضوع مستند نشده

Mathematical models, Problems, exercises, etc.

موضوع مستند نشده

Mathematical models.

موضوع مستند نشده

Mathematical statistics, Problems, exercises, etc.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

R (Computer program language)

موضوع مستند نشده

Statistics.

موضوع مستند نشده

Maschinelles Lernen

موضوع مستند نشده

Mathematical models.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

Modèles mathématiques-- Problèmes et exercices.

موضوع مستند نشده

Modèles mathématiques.

موضوع مستند نشده

R (Computer program language)

موضوع مستند نشده

Statistics.

موضوع مستند نشده

Statistik

موضوع مستند نشده

Statistik

موضوع مستند نشده

Statistique mathématique-- Problèmes et exercices.

موضوع مستند نشده

Statistique mathématique.

موضوع مستند نشده

QA

شماره

ويراست

شماره رده

نشانه اثر

شماره رده

کد سيستم

مستند نام اشخاص تاييد نشده

Hastie, Trevor

مستند نام اشخاص تاييد نشده

James, Gareth, (Gareth Michael)

مستند نام اشخاص تاييد نشده

Tibshirani, Robert

مستند نام اشخاص تاييد نشده

Witten, Daniela

تاريخ عمليات

20201221082812.0

قواعد فهرست نويسي ( بخش توصيفي )

rda

نام الکترونيکي

نوع ماده

[Book]

کد کاربرگه

270410

تكميل شده

Y