Random forest prediction method based on optimization of fruit fly

被引：0
|
作者：
Zhao D. [1 ,2 ]
Zang X.-B. [1 ]
Zhao H.-W. [1 ]
机构：
[1] College of Computer Science and Technology, Jilin University, Changchun
[2] College of Computer Science and Technology, Changchun Normal University, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2017年 / 47卷 / 02期
关键词：
Computer application; Machine learning; Optimization of fruit fly; Random forest;
D O I：
10.13229/j.cnki.jdxbgxb201702036
中图分类号：
学科分类号：
摘要：
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. © 2017, Editorial Board of Jilin University. All right reserved.
引用
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页码：609 / 614
页数：5
相关论文
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