Supervised machine learning : (Record no. 16493)
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| 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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