吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (2): 609-614.doi: 10.13229/j.cnki.jdxbgxb201702036

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Random forest prediction method based on optimization of fruit fly

ZHAO Dong1, 2, ZANG Xue-bai1, ZHAO Hong-wei1   

  1. 1.College of Computer Science and Technology, Jilin University,Changchun 130022,China;
    2.College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China
  • Received:2016-01-12 Online:2017-03-20 Published:2017-03-20

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Abstract: This paper presents a random forest prediction method based on optimization of fruit fly. This method uses fruit fly optimization algorithm to optimize the two main parameters of random forest; then, constructs a random forest optimization model. The proposed method and existing methods are compared and analyzed. Experimental results show that the proposed method not only has higher recognition accuracy, but also has high efficiency in time, and can be used as an effective tool for prediction problem.

Key words: computer application, machine learning, optimization of fruit fly, random forest

CLC Number: 

  • TP393
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