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Artificial Bee Colony based Data Mining Algorithms for Classification Tasks

Author

Listed:
  • Mohd Afizi Mohd Shukran
  • Yuk Chung
  • Wei-Chang Yeh
  • Noorhaniza Wahid
  • Ahmad Mujahid Ahmad Zaidi

Abstract

Artificial Bee Colony (ABC) algorithm is considered new and widely used in searching for optimum solutions. This is due to its uniqueness in problem-solving method where the solution for a problem emerges from intelligent behaviour of honeybee swarms. This paper proposes the use of the ABC algorithm as a new tool for Data Mining particularly in classification tasks. Moreover, the proposed ABC for Data Mining were implemented and tested against six traditional classification algorithms classifiers. From the obtained results, ABC proved to be a suitable candidate for classification tasks. This can be proved in the experimental result where the performance of the proposed ABC algorithm has been tested by doing the experiments using UCI datasets. The results obtained in these experiments indicate that ABC algorithm are competitive, not only with other evolutionary techniques, but also to industry standard algorithms such as PART, SOM, Naive Bayes, Classification Tree and Nearest Neighbour (kNN), and can be successfully applied to more demanding problem domains.

Suggested Citation

  • Mohd Afizi Mohd Shukran & Yuk Chung & Wei-Chang Yeh & Noorhaniza Wahid & Ahmad Mujahid Ahmad Zaidi, 2011. "Artificial Bee Colony based Data Mining Algorithms for Classification Tasks," Modern Applied Science, Canadian Center of Science and Education, vol. 5(4), pages 217-217, August.
    • Handle: RePEc:ibn:masjnl:v:5:y:2011:i:4:p:217
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    References listed on IDEAS

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    1. Sikora, Riyaz & Piramuthu, Selwyn, 2007. "Framework for efficient feature selection in genetic algorithm based data mining," European Journal of Operational Research, Elsevier, vol. 180(2), pages 723-737, July.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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