Evaluating loss minimization in multi-label classification via stochastic simulation using beta distribution

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dc.contributor.advisor-co1Rodrigues, Alexandre Loureiros
dc.contributor.advisor1Varejão, Flávio Miguel
dc.contributor.authorMello, Lucas Henrique Sousa
dc.contributor.referee1Rauber, Thomas Walter
dc.contributor.referee2Carvalho, Alexandre Plastino de
dc.date.accessioned2016-08-29T15:33:25Z
dc.date.available2016-07-11
dc.date.available2016-08-29T15:33:25Z
dc.date.issued2016-05-20
dc.description.abstractabstracteng
dc.description.resumoThe objective of this work is to present the effectiveness and efficiency of algorithms for solving the loss minimization problem in Multi-Label Classification (MLC). We first prove that a specific case of loss minimization in MLC isNP-complete for the loss functions Coverage and Search Length, and therefore,no efficient algorithm for solving such problems exists unless P=NP. Furthermore, we show a novel approach for evaluating multi-label algorithms that has the advantage of not being limited to some chosen base learners, such as K-neareast Neighbor and Support Vector Machine, by simulating the distribution of labels according to multiple Beta Distributions.
dc.formatText
dc.identifier.citationMELLO, Lucas Henrique Sousa. Evaluating loss minimization in multi-label classification via stochastic simulation using beta distribution. 2016. Dissertação (Mestrado em Informática) - Universidade Federal do Espírito Santo, Centro Tecnológico, Vitória, 2016.
dc.identifier.urihttps://dspace5.ufes.br/handle/10/4309
dc.languagepor
dc.publisherUniversidade Federal do Espírito Santo
dc.publisher.countryBR
dc.publisher.courseMestrado em Informática
dc.publisher.departmentCentro Tecnológico
dc.publisher.initialsUFES
dc.publisher.programPrograma de Pós-Graduação em Informática
dc.rightsopen access
dc.subjectControle de perdaspor
dc.subjectAprendizado multirrótulopor
dc.subject.br-rjbnAprendizado do computador
dc.subject.br-rjbnOtimização matemática
dc.subject.br-rjbnClassificação
dc.subject.br-rjbnAlgoritmos
dc.subject.cnpqCiência da Computação
dc.subject.udc004
dc.titleEvaluating loss minimization in multi-label classification via stochastic simulation using beta distribution
dc.typemasterThesis

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