TY - GEN A1 - Fernández, Maria C. A1 - Menasalvas, Ernestina A1 - Marbán, Óskar A1 - Pena, José M. A1 - Millán, Socorro A2 - Grzymala-Busse, Jerzy - ed. A2 - Świniarski, Roman W. - ed. A2 - Zhong, Ning - ed. A2 - Ziarko, Wojciech - ed. PB - Zielona Góra: Uniwersytet Zielonogórski N2 - 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. N2 - 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. L1 - http://www.zbc.uz.zgora.pl/Content/58785/AMCS_2001_11_3_8.pdf L2 - http://www.zbc.uz.zgora.pl/Content/58785 KW - rough sets KW - rough dependencies KW - association rules KW - Apriori algorithm KW - minimal decision rules T1 - Minimal decision rules based on the Apriori algorithm UR - http://www.zbc.uz.zgora.pl/dlibra/docmetadata?id=58785 ER -