Exploring the data using Extended Association Rule Network
Carregando...
Fontes externas
Fontes externas
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Ieee
Institute of Electrical and Electronics Engineers (IEEE)
Institute of Electrical and Electronics Engineers (IEEE)
Tipo
Trabalho apresentado em evento
Direito de acesso
Acesso aberto
Fontes externas
Fontes externas
Resumo
In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.
Descrição
Idioma
Inglês
Citação
2018 7th Brazilian Conference On Intelligent Systems (bracis). New York: Ieee, p. 330-335, 2018.
