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An introduction to statistical learning: with applications in R (Record no. 5158)

MARC details
000 -LEADER
fixed length control field 01764nam a22002297a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20241211163246.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241211b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781071614204
040 ## - CATALOGING SOURCE
Transcribing agency National Institute of Technology Goa
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Item number JAM/INT
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name James, Gareth
110 ## - MAIN ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Witten, Daniela
111 ## - MAIN ENTRY--MEETING NAME
Meeting name or jurisdiction name as entry element Hastie, Trevor
245 ## - TITLE STATEMENT
Title An introduction to statistical learning: with applications in R
250 ## - EDITION STATEMENT
Edition statement 2nd
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York:
Name of publisher, distributor, etc. Springer,
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent xx, 608p.: 6x11x2; Paperback
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, deep learning, survival analysis, multiple testing, 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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term Mathematics
Topical term or geographic name entry element Mathematics; R Computer program language; Mathematical statistics; Linear regression; Resampling methods
700 ## - 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 Books
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total checkouts Full call number Barcode Date last seen Price effective from Koha item type Public note Date due Date last checked out
    Dewey Decimal Classification     Central Library NIT Goa Central Library NIT Goa General stacks 11/12/2024 Atlantic Publishers & Distributors (P) Ltd. 5645.00   519.5 JAM/INT 10826 11/12/2024 11/12/2024 Reference Reference Book Rack number 38(B)    
    Dewey Decimal Classification     Central Library NIT Goa Central Library NIT Goa General stacks 11/12/2024 Atlantic Publishers & Distributors (P) Ltd. 5645.00   519.5 JAM/INT 10827 11/12/2024 11/12/2024 Books Book Rack number 11(A)    
    Dewey Decimal Classification     Central Library NIT Goa Central Library NIT Goa General stacks 11/12/2024 Atlantic Publishers & Distributors (P) Ltd. 5645.00 1 519.5 JAM/INT 10828 24/04/2025 11/12/2024 Books Book Rack number 11(A) 23/07/2025 24/04/2025
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