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An Introduction to Statistical Learning (Record no. 86446)

MARC details
000 -LEADER
fixed length control field 03473nam a22004817a 4500
001 - CONTROL NUMBER
control field sulb0079947
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20241007182806.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130625s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461471387
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-7138-7
Source of number or code doi
040 ## - CATALOGING SOURCE
Original cataloging agency BD-SySUS
Transcribing agency BD-SySUS
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
Subject category code MAT029000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
Item number JAI
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name James, Gareth.
Relator term author.
9 (RLIN) 67913
245 13 - TITLE STATEMENT
Title An Introduction to Statistical Learning
Remainder of title with Applications in R /
Statement of responsibility, etc. by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 426 p. 150 illus., 146 illus. in color.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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.
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 Statistics.
9 (RLIN) 67914
Topical term or geographic name as entry element Artificial intelligence.
9 (RLIN) 67915
Topical term or geographic name as entry element Statistics.
9 (RLIN) 67916
Topical term or geographic name as entry element Statistical Theory and Methods.
9 (RLIN) 67917
Topical term or geographic name as entry element Statistics and Computing/Statistics Programs.
9 (RLIN) 67918
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
9 (RLIN) 67919
Topical term or geographic name as entry element Statistics, general.
9 (RLIN) 67920
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Witten, Daniela.
Relator term author.
9 (RLIN) 67921
Personal name Hastie, Trevor.
Relator term author.
9 (RLIN) 67922
Personal name Tibshirani, Robert.
Relator term author.
9 (RLIN) 67923
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
9 (RLIN) 67924
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9781461471370
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Central Library, SUST Central Library, SUST General Stacks 07/10/2024   519.5 JAI 0079947 07/10/2024 1 07/10/2024 Books
    Dewey Decimal Classification     Central Library, SUST Central Library, SUST General Stacks 07/10/2024   519.5 JAI 0079948 07/10/2024 2 07/10/2024 Books