Addressing class imbalance in multilabel Prototype Generation for k-Nearest Neighbor classification

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• dc.contributor.author Penarrubia, Carlos
• dc.contributor.author Valero-Mas, Jose J.
• dc.contributor.author Gallego, Antonio Javier
• dc.contributor.author Calvo-Zaragoza, Jorge
• dc.date.accessioned 2023-07-18T06:33:59Z
• dc.date.issued 2023
• dc.description Comunicació presentada a 11th Iberian Conference (IbPRIA 2023), celebrada del 27 al 30 de juny de 2023 a Alacant, Espanya.
• dc.description.abstract Prototype Generation (PG) methods seek to improve the efficiency of the k-Nearest Neighbor (kNN) classifier by obtaining a reduced version of a given reference dataset following certain heuristics. Despite being largely addressed topic in multiclass scenarios, few works deal with PG in multilabel environments. Hence, the existing proposals exhibit a number of limitations, being label imbalance one of paramount relevance as it constitutes a typical challenge of multilabel datasets. This work proposes two novel merging policies for multilabel PG schemes specifically devised for label imbalance, as well as a mechanism to prevent inappropriate samples from undergoing a reduction process. These proposals are applied to three existing multilabel PG methods—Multilabel Reduction through Homogeneous Clustering, Multilabel Chen, and Multilabel Reduction through Space Partitioning—and evaluated on 12 different data assortments with different degrees of label imbalance. The results prove that the proposals overcome—in some cases in a significant manner—those obtained with the original methods, hence validating the presented approaches and enabling further research lines on this topic.
• dc.description.sponsorship This work was supported by the I+D+i project TED2021-132103A-I00 (DOREMI), funded by MCIN/AEI/10.13039/501100011033.
• dc.format.mimetype application/pdf
• dc.identifier.citation Penarrubia C, Valero-Mas JJ, Gallego AJ, Calvo-Zaragoza J. Addressing class imbalance in multilabel Prototype Generation for k-Nearest Neighbor classification. In: Pertusa A, Gallego AJ, Sánchez JA, Domingues I, editors. Pattern recognition and image analysis: 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, proceedings; 2023 Jun 27-30; Alicante, Spain. Cham: Springer; 2023. p. 15-27. DOI: 10.1007/978-3-031-36616-1_2
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-031-36616-1_2
• dc.identifier.isbn 978-3-031-36615-4
• dc.identifier.issn 0302-9743
• dc.identifier.uri http://hdl.handle.net/10230/57600
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof Pertusa A, Gallego AJ, Sánchez JA, Domingues I, editors. Pattern recognition and image analysis: 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, proceedings; 2023 Jun 27-30; Alicante, Spain. Cham: Springer; 2023. p. 15-27.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/TED2021-132103A-I00
• dc.rights © Springer This is a author's accepted manuscript of: Penarrubia C, Valero-Mas JJ, Gallego AJ, Calvo-Zaragoza J. Addressing class imbalance in multilabel Prototype Generation for k-Nearest Neighbor classification. In: Pertusa A, Gallego AJ, Sánchez JA, Domingues I, editors. Pattern recognition and image analysis: 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, proceedings; 2023 Jun 27-30; Alicante, Spain. Cham: Springer; 2023. p. 15-27. The final version is available online at: http://dx.doi.org/10.1007/978-3-031-36616-1_2
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Multilabel Learning
• dc.subject.keyword Imbalanced classification
• dc.subject.keyword Prototype Generation
• dc.subject.keyword Efficient k-Nearest Neighbor
• dc.title Addressing class imbalance in multilabel Prototype Generation for k-Nearest Neighbor classification
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion