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Języki publikacji
Abstrakty
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.
Rocznik
Tom
Strony
691--704
Opis fizyczny
Bibliogr. 22 poz., tab., wykr.
Twórcy
autor
autor
autor
autor
autor
- DLSIIS Facultad de Informatica, U.P.M., Madrid, Spain, cfbaizan@fi.upm.es
Bibliografia
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0012-0032