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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
447-455

Parallel SVM algorithm based on Relief and bacterial foraging optimization algorithm

Hu Jian1,2
Wang Xiangtai1
Mao Yimin1
Liu Wei2
1. School of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China
2. Dept. of Information Engineering, Gannan University of Science & Technology, Ganzhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2021.08.0314

Abstract

Aiming at the problems of parallel support vector machine(SVM) algorithm in big data environment such as redundant data sensitivity, difficulty in parameter selection, and low parallelization efficiency, this paper proposed a parallel SVM algorithm using Relief and bacterial foraging optimization(BFO) algorithm based on MapReduce(RBFO-PSVM). Firstly, the algorithm designed a feature weight calculation strategy(MI-Relief), which used mutual information to improve the weight calculation function of Relief algorithm to eliminate redundant features in the data set and effectively reduce redundant data to support parallelism. Secondly, this paper proposed a hybrid BFO algorithm based on MapReduce(MR-HBFO), which selected the optimal parameters of SVM in parallel, and solved the problem of difficult selection of SVM parameters. Finally, it proposed the kernel clustering strategy(KCS) to reduce the size of the data set involved in parallel training, and proposed a cross-fusion cascaded parallel SVM(CFCPSVM) to improve the cascade SVM(CSVM) feedback mechanism. It trained SVM by combining with the MapReduce programming framework, and this improved the parallelization efficiency of parallel SVM. Experiments show that the RBFO-PSVM algorithm has a better classification effect on large data sets and is more suitable for large data environments.

Foundation Support

国家自然科学基金资助项目(41562019)
国家重点研发计划资助项目(2018YFC1504705)
江西省教育厅科技资助项目(GJJ209407,GJJ209405)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0314
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 447-455
Serial Number: 1001-3695(2022)02-021-0447-09

Publish History

[2021-12-17] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

胡健, 王祥太, 毛伊敏, 等. 基于Relief和BFO的并行支持向量机算法 [J]. 计算机应用研究, 2022, 39 (2): 447-455. (Hu Jian, Wang Xiangtai, Mao Yimin, et al. Parallel SVM algorithm based on Relief and bacterial foraging optimization algorithm [J]. Application Research of Computers, 2022, 39 (2): 447-455. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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