A genetic algorithm for classification

Authors:
Raul Robu;Stefan Holban
Affiliations:
Department of Automation and Applied Informatics, Department of Computers "Politehnica" University of Timisoara, Timisoara, Romania;Department of Automation and Applied Informatics, Department of Computers "Politehnica" University of Timisoara, Timisoara, Romania
Venue:
ICCC'11 Proceedings of the 2011 international conference on Computers and computing
Year:
2011

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Abstract

The paper presents aspects regarding genetic algorithms, their use in data mining and especially about their use in the discovery of classification rules. A synthetic presentation of the fitness functions of the genetic algorithms used for mining the classification rules is performed. A genetic algorithm with a new fitness function for mining the classification rules is suggested. The proposed algorithm was tested on classic dataset Car, Zoo and Mushroom. The same datasets were tested with classic algorithms NaiveBayes si J48. The results obtained by applying the three algorithms are presented.