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 |