An Introduction to Statistical Learning : (Record no. 34016)

MARC details
000 -LEADER
fixed length control field 03317nam a22004817a 4500
003 - CONTROL NUMBER IDENTIFIER
control field CUTN
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20201222112154.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201222b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461471370 (acidfree paper)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9781461471387 (eBook)
041 ## - LANGUAGE CODE
Language English
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
Item number JAM
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name James, Gareth.
245 03 - TITLE STATEMENT
Title An Introduction to Statistical Learning :
Remainder of title with applications in R /
Statement of responsibility, etc Gareth James,[et.al]
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New York, NY :
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc ©2013.
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 426 pages :
Other physical details illustrations (some color) ;
Dimensions 24 cm.
500 ## - GENERAL NOTE
General note Includes index.
505 ## - FORMATTED CONTENTS NOTE
Title 1. Introduction --
-- 2. Statistical Learning --
-- 3. Linear Regression --
-- 4. Classification --
-- 5. Resampling Methods --
-- 6. Linear Model Selection and Regularization --
-- 7. Moving Beyond Linearity --
-- 8. Tree-Based Methods --
-- 9. Support Vector Machines --
-- 10. Unsupervised Learning.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical models
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name James, Gareth,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Witten, Daniela,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hastie, Trevor,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tibshirani, Robert,
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type General Books
246 30 - VARYING FORM OF TITLE
Title proper/short title Statistical learning
490 1# - SERIES STATEMENT
Series statement Springer texts in statistics,
International Standard Serial Number 1431-875X ;
Volume number/sequential designation 103
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Form subdivision Problems, exercises, etc.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Form subdivision Problems, exercises, etc.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Springer texts in statistics ;
Volume number/sequential designation 103.
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c copycat
d 2
e ncip
f 20
g y-gencatlg
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Sciences 22/12/2020 5 5 519.5 JAM 42189 09/12/2023 20/10/2023 22/12/2020 General Books

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