An Automatic Programming ACO-Based Algorithm for Classification Rule Mining
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Autor
Olmo, J.L.
Luna, J.M.
Romero, J.R.
Ventura Soto, S.
Fecha
2017-01-20Materia
GBAPAlgorithm
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In this paper we present a novel algorithm, named GBAP, that jointly uses
automatic programming with ant colony optimization for mining classification rules.
GBAP is based on a context-free grammar that properly guides the search process of
valid rules. Furthermore, its most important characteristics are also discussed, such
as the use of two different heuristic measures for every transition rule, as well as the
way it evaluates the mined rules. These features enhance the final rule compilation
from the output classifier. Finally, the experiments over 17 diverse data sets prove
that the accuracy values obtained by GBAP are pretty competitive and even better
than those resulting from the top Ant-Miner algorithm