Machine Learning Methods with Noisy, Incomplete or Small Datasets (Record no. 46872)

MARC details
000 -LEADER
fixed length control field 04890naaaa2201261uu 4500
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control field https://directory.doabooks.org/handle/20.500.12854/76309
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220219220646.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number books978-3-0365-1287-7
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783036512884
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783036512877
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.3390/books978-3-0365-1287-7
Terms of availability doi
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title English
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Subject category code KNTX
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100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Solé-Casals, Jordi
Relationship edt
245 10 - TITLE STATEMENT
Title Machine Learning Methods with Noisy, Incomplete or Small Datasets
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Basel, Switzerland
Name of publisher, distributor, etc. MDPI - Multidisciplinary Digital Publishing Institute
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent 1 electronic resource (316 p.)
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open Access
Source of term star
Standardized terminology for access restriction Unrestricted online access
520 ## - SUMMARY, ETC.
Summary, etc. In many machine learning applications, available datasets are sometimes incomplete, noisy or affected by artifacts. In supervised scenarios, it could happen that label information has low quality, which might include unbalanced training sets, noisy labels and other problems. Moreover, in practice, it is very common that available data samples are not enough to derive useful supervised or unsupervised classifiers. All these issues are commonly referred to as the low-quality data problem. This book collects novel contributions on machine learning methods for low-quality datasets, to contribute to the dissemination of new ideas to solve this challenging problem, and to provide clear examples of application in real scenarios.
540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE
Terms governing use and reproduction Creative Commons
Use and reproduction rights https://creativecommons.org/licenses/by/4.0/
Source of term cc
-- https://creativecommons.org/licenses/by/4.0/
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Language note English
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Topical term or geographic name entry element Information technology industries
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Uncontrolled term open contours
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Uncontrolled term Extreme Learning Machines (ELM)
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Uncontrolled term small data-sets
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Uncontrolled term feature selection
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Uncontrolled term noise elimination
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Uncontrolled term noisy datasets
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Uncontrolled term Discriminant Analysis
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Uncontrolled term feature extraction
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Uncontrolled term non-negative matrix factorization
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Uncontrolled term feature elimination
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Uncontrolled term imperfect dataset
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Sun, Zhe
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Caiafa, Cesar F.
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Marti-Puig, Pere
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tanaka, Toshihisa
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Solé-Casals, Jordi
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Sun, Zhe
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Caiafa, Cesar F.
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Marti-Puig, Pere
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tanaka, Toshihisa
Relationship oth
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name www.oapen.org
Uniform Resource Identifier <a href="https://mdpi.com/books/pdfview/book/3727">https://mdpi.com/books/pdfview/book/3727</a>
Access status 0
Public note DOAB: download the publication
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name www.oapen.org
Uniform Resource Identifier <a href="https://directory.doabooks.org/handle/20.500.12854/76309">https://directory.doabooks.org/handle/20.500.12854/76309</a>
Access status 0
Public note DOAB: description of the publication

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