Minimal Decision Rules Based on the Apriori Algorithm

• Autorzy: Fernandez M. C. , Menasalvas E. , Marban O. , Pena J. M. , Millan S.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

rough sets; rough dependencies; association rules; apriori algorithm; minimal decision rules

PL

baza danych; algorytmy

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2001
• Tom: Vol. 11, no 3
• Strony: 691--704
• Opis fizyczny: Bibliogr. 22 poz., tab., wykr.

Twórcy

autor

Fernandez M. C.

autor

Menasalvas E.

autor

Marban O.

autor

Pena J. M.

autor

Millan S.

• DLSIIS Facultad de Informatica, U.P.M., Madrid, Spain,