Supervised machine learning : (Record no. 16493)

MARC details
000 -LEADER
fixed length control field 03889cam a2200589Ki 4500
001 - CONTROL NUMBER
control field 9780429297595
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220724194335.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu---unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201023t20212021flu ob 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency OCoLC-P
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429297595
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429297599
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000176810
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000176819
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000176827
Qualifying information electronic book
-- Mobipocket
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000176827
Qualifying information electronic book
-- Mobipocket
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000176834
Qualifying information electronic book
-- EPUB
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000176835
Qualifying information electronic book
-- EPUB
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367538828
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367277321
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1201337174
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1201337174
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.75
Item number .K65 2021eb
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 037000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 077000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/1
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kolosova, Tanya,
Relator term author.
245 10 - TITLE STATEMENT
Title Supervised machine learning :
Remainder of title optimization framework and applications with SAS and R /
Statement of responsibility, etc. Tanya Kolosova and Samuel Berestizhevsky.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Boca Raton, FL :
Name of producer, publisher, distributor, manufacturer CRC Press,
Date of production, publication, distribution, manufacture, or copyright notice 2021.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2021
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xxiv, 160 pages).
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
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note IntroductionPART 1Introduction to the AI frameworkSupervised Machine Learning and Its Deployment in SAS and RBootstrap methods and Its Deployment in SAS and ROutliers Detection and Its Deployment in SAS and RDesign of Experiment and Its Deployment in SAS and RPART IIIntroduction to the SAS and R based table-driven environmentInput Data componentDesign of Experiment for Machine-Learning component"Contaminated" Training Datasets ComponentPART IIIInsurance Industry: Underwriters decision-making processInsurance Industry: Claims Modeling and PredictionIndex
520 ## - SUMMARY, ETC.
Summary, etc. AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI framework comprises of bootstrapping to create multiple training and testing data sets with various characteristics, design and analysis of statistical experiments to identify optimal feature subsets and optimal hyper-parameters for ML methods, data contamination to test for the robustness of the classifiers. Key Features: Using ML methods by itself doesn't ensure building classifiers that generalize well for new data Identifying optimal feature subsets and hyper-parameters of ML methods can be resolved using design and analysis of statistical experiments Using a bootstrapping approach to massive sampling of training and tests datasets with various data characteristics (e.g.: contaminated training sets) allows dealing with bias Developing of SAS-based table-driven environment allows managing all meta-data related to the proposed AI framework and creating interoperability with R libraries to accomplish variety of statistical and machine-learning tasks Computer programs in R and SAS that create AI framework are available on GitHub
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Supervised learning (Machine learning)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Program transformation (Computer programming)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SAS (Computer program language)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element R (Computer program language)
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTERS / Machine Theory
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTERS / Mathematical & Statistical Software
Source of heading or term bisacsh
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Berestizhevsky, Samuel,
Relator term author.
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Read Online
Uniform Resource Identifier <a href="https://www.taylorfrancis.com/books/9780429297595">https://www.taylorfrancis.com/books/9780429297595</a>
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified OCLC metadata license agreement
Uniform Resource Identifier <a href="http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf">http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type eBook

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