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Boosting the performance of over-sampling algorithms through under-sampling the minority class

journal contribution

posted on 2019-05-01, 00:00 authored by Romero F A B de Morais, Germano C Vasconcelos

Boosting the performance of over-sampling algorithms through under-sampling the minority class

History

Journal

Neurocomputing

Volume

343

Pagination

3 - 18

Publisher

Elsevier

Location

Amsterdam, The Netherlands

Publisher DOI

https://doi.org/10.1016/j.neucom.2018.04.088

ISSN

0925-2312

eISSN

1872-8286

Language

eng

Author URL

http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000464603600002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7

Publication classification

C1 Refereed article in a scholarly journal

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Keywords

Computer Science Computer Science, Artificial Intelligence IMBALANCED CLASSIFICATION Imbalanced learning Noisy data Over-sampling Science & Technology SMOTE Technology Under-sampling

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All Rights Reserved

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