Minimal Decision Rules Based on the A Priori Algorithm
Covadonga Fernández Baizán, Ernestina Menasalvas, Óscar Marbán Gallego, Jose Maria Peña Sanchez, Socorro Millán · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2001
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 comprehensi- ble (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 ap- proach, 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.