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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 7
2081-2084,2090

Feature transformation method fusing minimum principal component subspaces of each class

Yang Zhongliang1,2
Li Mengmeng1,2
Xu Ruohao1,2
Yang Lifang1,2
Shang Zhigang1,2
1. School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
2. Henan Key Laboratory of Brain Science & Brain-Computer Interface Technology, Zhengzhou 450001, China
DOI: 10.19734/j.issn.1001-3695.2020.08.0219

Abstract

Aiming at the problems that principal component analysis was unable to use the class information of the samples and the direction of the maximum principal component was likely to cause overlap of the samples from different classes, this paper proposed a feature transformation method fusing minimum principal component subspaces of different classes. Firstly, the proposed method analyzed the component of each class of data; and then it fused the projection results of the original data in all subspaces to form a new feature space; finally, this paper used the KEEL benchmark database to test the method. The results show that the proposed method can construct a feature space that is more conducive to classification compared with other feature transformation methods, which can help to improve the classification accuracy of the classifier.

Foundation Support

国家自然科学基金资助项目(U1304602)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.08.0219
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 7
Section: Algorithm Research & Explore
Pages: 2081-2084,2090
Serial Number: 1001-3695(2021)07-030-2081-04

Publish History

[2021-07-05] Printed Article

Cite This Article

杨中良, 李蒙蒙, 徐若灏, 等. 一种融合各类最小主成分子空间的特征变换方法 [J]. 计算机应用研究, 2021, 38 (7): 2081-2084,2090. (Yang Zhongliang, Li Mengmeng, Xu Ruohao, et al. Feature transformation method fusing minimum principal component subspaces of each class [J]. Application Research of Computers, 2021, 38 (7): 2081-2084,2090. )

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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