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dc.creatorSaalim, Mehsun Ihtiyanes_ES
dc.date.accessioned2023-09-20T11:20:38Z
dc.date.available2023-09-20T11:20:38Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/2454/46374
dc.description.abstractThis study aims to implement, analyze, and compare the effectiveness of a novel technique known as Perturbation-Based Oversampling (POS). This technique is designed to address class imbalance in machine learning by augmenting the minority class instances by strategically perturbing features using a hyperparameter ’p’. Two additional variations, namely POS 1.0 and POS 2.0, have been proposed as extensions of the original POS approach. Detailed experiments have been conducted across diverse datasets, presenting a comprehensive performance evaluation in terms of precision when compared to a selection of established methods designed to tackle unbalanced classification challenges.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectClassificationen
dc.subjectImbalanced problemsen
dc.subjectOversamplingen
dc.subjectFeaturesen
dc.subjectImbalanced ratioen
dc.subjectPerturbationen
dc.titleStudying the perturbation-based oversampling technique for imbalanced classification problemsen
dc.typeTrabajo Fin de Grado/Gradu Amaierako Lanaes
dc.typeinfo:eu-repo/semantics/bachelorThesisen
dc.date.updated2023-09-19T10:37:18Z
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería Industrial, Informática y de Telecomunicaciónes_ES
dc.contributor.affiliationIndustria, Informatika eta Telekomunikazio Ingeniaritzako Goi Mailako Eskola Teknikoaeu
dc.description.degreeGraduado o Graduada en Ingeniería Informática por la Universidad Pública de Navarra (Programa Internacional)es_ES
dc.description.degreeInformatika Ingeniaritzan Graduatua Nafarroako Unibertsitate Publikoan (Nazioarteko Programa)eu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.contributor.advisorTFESanz Delgado, José Antonioes_ES


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El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
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