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A bias correction function for classification performance assessment in two-class imbalanced problems
dc.contributor.author | García, Vicente | |
dc.contributor.author | Mollineda, Ramón A. | |
dc.contributor.author | Sánchez Garreta, Josep Salvador | |
dc.date.accessioned | 2015-07-22T07:43:25Z | |
dc.date.available | 2015-07-22T07:43:25Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | GARCÍA, Vicente; MOLLINEDA, Ramón A.; SÁNCHEZ, J. Salvador. A bias correction function for classification performance assessment in two-class imbalanced problems. Knowledge-Based Systems, 2014, vol. 59, p. 66-74. | ca_CA |
dc.identifier.issn | 0950-7051 | |
dc.identifier.issn | 1872-7409 | |
dc.identifier.uri | http://hdl.handle.net/10234/128466 | |
dc.description.abstract | This paper introduces a framework that allows to mitigate the impact of class imbalance on most scalar performance measures when used to evaluate the behavior of classifiers. Formally, a correction function is defined with the aim of highlighting those classification results that present moderately higher prediction rates on the minority class. Besides, this function punishes those scenarios that are biased towards the majority class, but also those that are strongly biased to favor the minority class. This strategy assumes a typical imbalance task, in which the minority class contains the most relevant samples to the research purposes. A novel experimental framework is designed to show the advantages of our approach when compared to the standard use of well-established measures, demonstrating its consistency and validity. | ca_CA |
dc.description.sponsorShip | This work has partially been supported by the Spanish Ministry of Education and Science under Grant TIN2009-14205, the Universitat Jaume I under Grant P1-1B2012-22, the Mexican National Council for Science and Technology (CONACyT), and the Generalitat Valenciana under Grant PROMETEO/2010/028. | ca_CA |
dc.format.extent | 9 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.relation.isPartOf | Knowledge-Based Systems, 2014, vol. 59 | ca_CA |
dc.rights | Copyright © 2014 Elsevier B.V. | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | class imbalance | ca_CA |
dc.subject | performance measure | ca_CA |
dc.subject | classification | ca_CA |
dc.subject | geometric mean | ca_CA |
dc.subject | accuracy | ca_CA |
dc.subject | evaluation | ca_CA |
dc.title | A bias correction function for classification performance assessment in two-class imbalanced problems | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | http://dx.doi.org/10.1016/j.knosys.2014.01.021 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | http://www.sciencedirect.com/science/article/pii/S0950705114000380 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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