Minimal decision rules based on the apriori algorithm

María Fernández; Ernestina Menasalvas; Óscar Marbán; José Peña; Socorro Millán

International Journal of Applied Mathematics and Computer Science (2001)

  • Volume: 11, Issue: 3, page 691-704
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Fernández, María, et al. "Minimal decision rules based on the apriori algorithm." International Journal of Applied Mathematics and Computer Science 11.3 (2001): 691-704. <http://eudml.org/doc/207527>.

@article{Fernández2001,
abstract = {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.},
author = {Fernández, María, Menasalvas, Ernestina, Marbán, Óscar, Peña, José, Millán, Socorro},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {association rules; minimal decision rules; Apriori algorithm; rough sets; rough dependencies; decision rules; rough set},
language = {eng},
number = {3},
pages = {691-704},
title = {Minimal decision rules based on the apriori algorithm},
url = {http://eudml.org/doc/207527},
volume = {11},
year = {2001},
}

TY - JOUR
AU - Fernández, María
AU - Menasalvas, Ernestina
AU - Marbán, Óscar
AU - Peña, José
AU - Millán, Socorro
TI - Minimal decision rules based on the apriori algorithm
JO - International Journal of Applied Mathematics and Computer Science
PY - 2001
VL - 11
IS - 3
SP - 691
EP - 704
AB - 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.
LA - eng
KW - association rules; minimal decision rules; Apriori algorithm; rough sets; rough dependencies; decision rules; rough set
UR - http://eudml.org/doc/207527
ER -

References

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