A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics

dc.contributor.advisorOliveira, Laura Emmanuella Alves dos Santos Santana de
dc.contributor.advisor-co1Márjory Da Costa Abreupt_BR
dc.contributor.authorNascimento, Tuany Mariah Lima do
dc.contributor.referees1Oliveira, Josenalde Barbosa de
dc.contributor.referees2Araújo, Daniel Sabino Amorim de
dc.date.accessioned2019-07-01T12:07:15Z
dc.date.accessioned2021-09-22T14:24:47Z
dc.date.available2019-07-01T12:07:15Z
dc.date.available2021-09-22T14:24:47Z
dc.date.issued2019-06-10
dc.description.resumoDue to the continuous use of social networks, users can be vulnerable to situations such as paedophilia treats. One of the ways to do the investigation of an alleged paedophile is to verify the legitimacy of the genre that it is said to be. One possible technique to adopt is keystroke dynamics analysis. However, this technique can extract many attributes, causing a negative impact on the accuracy of the classifier due to the presence of redundant and irrelevant attributes. Therefore, the present work presents a comparative analysis between two attribute selection approaches, wrapper and hybrid (wrapper + filter), using the metaheuristic genetic algorithm, as KNN, SVM, and Naive Bayes classifiers and as Correlation and Relief filter. Bringing the best SVM classifier using the wrapper approach, for both databases.pt_BR
dc.description.sponsorshipCNPqpt_BR
dc.identifier20160144419pt_BR
dc.identifier.citationNASCIMENTO, Tuany Mariah Lima do. A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics. 2019. 36f. Trabalho de Conclusão de Curso (Graduação em Análise e Desenvolvimento de Sistemas) - Unidade Acadêmica Especializada em Ciências Agrárias, Universidade Federal do Rio Grande do Norte, Macaíba, 2019.pt_BR
dc.identifier.urihttps://repositorio.ufrn.br/handle/123456789/37908
dc.languageenpt_BR
dc.publisherUniversidade Federal do Rio Grande do Nortept_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentAnálise e Desenvolvimento de Sistemaspt_BR
dc.publisher.initialsUFRNpt_BR
dc.subjectgender recognitionpt_BR
dc.subjectfeatures selectionpt_BR
dc.subjectgenetic algorithmspt_BR
dc.titleA Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamicspt_BR
dc.typebachelorThesispt_BR

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