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Minimal Decision Rules Based on the Apriori Algorithm
International Journal of Applied Mathematics and Computer Science, Tome 11 (2001) no. 3, pp. 691-704 Cet article a éte moissonné depuis la source Library of Science

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Based on rough set theory many algorithms for rules extraction from data have been proposed. Decision rules can be obtained directly from a database. Some condition values may be unnecessary in a decision rule produced directly from the database. Such values can then be eliminated to create a more comprehensible (minimal) rule. Most of the algorithms that have been proposed to calculate minimal rules are based on rough set theory or machine learning. In our approach, in a post-processing stage, we apply the Apriori algorithm to reduce the decision rules obtained through rough sets. The set of dependencies thus obtained will help us discover irrelevant attribute values.
Keywords: rough sets, rough dependencies, association rules, a priori algorithm, minimal decision rules
Mots-clés : baza danych, algorytmy 
@article{IJAMCS_2001_11_3_a7,
     author = {Fernandez, M. C. and Menasalvas, E. and Marban, O. and Pena, J. M. and Millan, S.},
     title = {Minimal {Decision} {Rules} {Based} on the {Apriori} {Algorithm}},
     journal = {International Journal of Applied Mathematics and Computer Science},
     pages = {691--704},
     year = {2001},
     volume = {11},
     number = {3},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/IJAMCS_2001_11_3_a7/}
}
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Fernandez, M. C.; Menasalvas, E.; Marban, O.; Pena, J. M.; Millan, S. Minimal Decision Rules Based on the Apriori Algorithm. International Journal of Applied Mathematics and Computer Science, Tome 11 (2001) no. 3, pp. 691-704. http://geodesic.mathdoc.fr/item/IJAMCS_2001_11_3_a7/