Publicação: Exploring the data using Extended Association Rule Network
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Data
2018-01-01
Orientador
Coorientador
Pós-graduação
Curso de graduação
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Editor
Ieee
Tipo
Trabalho apresentado em evento
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Acesso aberto
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.
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Idioma
Inglês
Como citar
2018 7th Brazilian Conference On Intelligent Systems (bracis). New York: Ieee, p. 330-335, 2018.
