Pattern Mining with Genetic Algorithms

  • Sebastián Ventura
  • José María Luna


This chapter describes the use of genetic algorithms for the mining of patterns of interest and the extraction of accurate relationships between them. The current chapter first makes an analysis of the utility of genetic algorithms in the mining of patterns of interest, paying special attention to the computational time and the memory requirements. Then, it describes general issues for any genetic algorithm in the pattern mining field, explaining different ways of representing patterns such as the one used to extract continuous patterns, which include richer information. Additionally, different genetic operators and fitness functions are properly described, denoting their usefulness in the mining of both patterns of interest and accurate associations. Then, different algorithmic approaches in the pattern mining field are analysed. Finally, this chapter deals with a series of application domains in which genetic algorithms for mining either patterns and association rules have been successfully applied.


Fitness Function Association Rule Genetic Operator Pattern Mining Continuous Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sebastián Ventura
    • 1
  • José María Luna
    • 1
  1. 1.Department of Computer Science and Numerical AnalysisUniversity of CordobaCordobaSpain

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