Minimal decision rules based on the apriori algorithm

• Autorzy: María C. Fernández , Ernestina Menasalvas , Óscar Marbán , José M. Peña , Socorro Millán
• 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

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

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2001
• Tom: 11
• Numer: 3
• Strony: 691-704

Daty

wydano

2001

otrzymano

2001-03-01

poprawiono

2001-06-01

Twórcy

autor

María C. Fernández

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

autor

Ernestina Menasalvas

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

autor

Óscar Marbán

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

autor

José M. Peña

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

autor

Socorro Millán

• Universidad del Valle, Cali, Colombia

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