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Algorithm Research & Explore
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982-985

ML-KNN algorithm based on nearest neighbor distance weight

Lu Kai
Xu Hua
School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Abstract

In the big data environment, the problem of high time complexity of multi-label K-nearest neighbor(ML-KNN) is particularly prominent. In addition, ML-KNN does not consider the effect of K nearest neighbors on the final classification results. This paper first clustered the training set, and then found a nearest cluster as new training set for test dataset. Then it calculated nearest neighbor distance weight, by which the effect of k neighbors was described. Finally, an unseen sample could be classified by this new method. Numerical simulation results in different datasets show that the proposed algorithm obtained a better classification result and improved the time complexity of the algorithm.

Foundation Support

国家教育部—新华三集团“云数融合”基金资助项目(2017A13055)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0738
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Algorithm Research & Explore
Pages: 982-985
Serial Number: 1001-3695(2020)04-005-0982-04

Publish History

[2020-04-05] Printed Article

Cite This Article

陆凯, 徐华. 基于最近邻距离权重的ML-KNN算法 [J]. 计算机应用研究, 2020, 37 (4): 982-985. (Lu Kai, Xu Hua. ML-KNN algorithm based on nearest neighbor distance weight [J]. Application Research of Computers, 2020, 37 (4): 982-985. )

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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