Abstract
In this paper, we extend monotone monomials as large itemsets in association rule mining to monotone DNF formulas. First, we introduce not only the minimum support but also the maximum overlap, which is a new measure how much all pairs of two monomials in a monotone DNF formula commonly cover data. Next, we design the algorithm dnf_cover to extract coverings as monotone DNF formulas satisfying both the minimum support and the maximum overlap. In the algorithm dnf_cover, first we collect the monomials of which support value is not only more than the minimum support but also less than the minimum support as seeds. Secondly we construct the coverings as monotone DNF formulas, by combining monomials in seeds under the minimum support and the maximum overlap. Finally, we apply the algorithm dnf_cover to bacterial culture data.
This work is partially supported by Japan Society for the Promotion of Science, Grants-in-Aid for Encouragement of Young Scientists (B) 15700137 and for Scientific Research (B) 13558036.
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Hirata, K., Nagazumi, R., Harao, M. (2003). Extraction of Coverings as Monotone DNF Formulas. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_15
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DOI: https://doi.org/10.1007/978-3-540-39644-4_15
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