吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (1): 252-258.doi: 10.13229/j.cnki.jdxbgxb201601038

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Adaptive artificial bee colony algorithm for classification problem

MA An-xiang, ZHANG Chang-sheng, ZHANG Bin, ZHANG Xiao-hong   

  1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2014-05-22 Online:2016-01-30 Published:2016-01-30

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Abstract: Appropriate rule evaluation functions are important to improve the performance of classification algorithm based on rules. In order to obtain the comprehensible classification rules, an adaptive artificial bee colony algorithm, called A_ABC algorithm, is proposed. The A_ABC algorithm can adaptively select a appropriate rule evaluation function for the given data, and effectively process both discrete attributes and continuous attributes. The proposed A_ABC algorithm is evaluated by experiment using different standard real datasets, and compared with existing classification algorithms. Results show that the A_ABC algorithm can solve classification problems more effectively than the existing algorithms.

Key words: artificial intelligence, adaptive artificial bee colony algorithm, classification problem, rule evaluation function

CLC Number: 

  • TP18
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