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Minimal decision rules based on the apriori algorithm

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Fernández M. C., Menasalvas E., Marbán Ó., Peña J. M., Millán S.

International Journal of Applied Mathematics and Computer Science

2001

tom 11

nr 3

691-704

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.

Ograniczanie wyników

1 International Journal of Applied Mathematics and Computer Science

1 Fernández M. C.

1 Marbán Ó.

1 Menasalvas E.

1 Millán S.

1 Peña J. M.

1 2001

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Minimal decision rules based on the apriori algorithm