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Algorithm Research & Explore
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1355-1359,1364

Attribute inconsistency weighted K nearest neighbor classification method

Xu Zheng
Deng Ansheng
Qu Yanpeng
College of Information Science & Technology, Dalian Maritime University, Dalian Liaoning 116026, China

Abstract

When calculating the similarity between samples, the conventional KNN algorithm deems each attribute equally important, and ignores the distinction of the attributes' significance. In order to address this issue, this paper employed the earth mover's distance to calculate the weight of each condition attribute. Firstly, this method divided two distributions according to the nearest neighbor relationship. Then, it designed an evaluation function based on earth mover's distance to gauge the inconsistency degree between the neighborhood of each sample with regard to each attribute and its equivalent refinement induced by the decision attribute. Last, it transformed the inconsistency degree to the significance of the corresponding attribute to implement an attribute weighted KNN. Through systematic experiments on several datasets, it verifies that the proposed method is insensitive to parameters and can significantly improve the classification performance of KNN, and outperforms some state-of-the-art classification methods. The results show that this method can select more accurate nearest neighbor samples by attribute weighting, and can be widely used in methods based on nearest neighbor.

Foundation Support

大连市青年科技之星资助项目(2018RQ70)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.07.0179
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Algorithm Research & Explore
Pages: 1355-1359,1364
Serial Number: 1001-3695(2021)05-013-1355-05

Publish History

[2021-05-05] Printed Article

Cite This Article

徐政, 邓安生, 曲衍鹏. 一种属性不一致性加权的K近邻分类方法 [J]. 计算机应用研究, 2021, 38 (5): 1355-1359,1364. (Xu Zheng, Deng Ansheng, Qu Yanpeng. Attribute inconsistency weighted K nearest neighbor classification method [J]. Application Research of Computers, 2021, 38 (5): 1355-1359,1364. )

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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