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CEC
2007
IEEE

Evolution of classification rules for comprehensible knowledge discovery

10 years 3 months ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classifiers), has three main features: it applies genetic programming to perform a search in the space of potential solutions; a procedure allows biasing the search towards regions of comprehensible hypothesis with high predictive quality and it includes a strategy for the selection of an optimum subset of rules (classifier) from the rules obtained as the result of the evolutionary process. A comparative study between this method and the rule induction algorithm C5.0 is carried out for two application problems (data sets). Experimental results show the advantages of using the method proposed.
Emiliano Carreno, Guillermo Leguizamón, Nea
Added 12 Aug 2010
Updated 12 Aug 2010
Type Conference
Year 2007
Where CEC
Authors Emiliano Carreno, Guillermo Leguizamón, Neal Wagner
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