JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2019, Vol. 54 ›› Issue (3): 102-109.doi: 10.6040/j.issn.1671-9352.1.2018.107

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Fixed-radius nearest neighbor progressive competition algorithm for imbalanced classification

ZHOU Peng1,2, YI Jing1,3, ZHU Zhen-fang4, LIU Pei-yu1,2*   

  1. 1. School of Information Science &
    Engineering, Shandong Normal University, Jinan 250358, Shandong, China;
    2. Shandong ProvincialKey Laboratory for Distributed Computer Software Novel Technology, Jinan 250358, Shandong, China;
    3. School of Computer Science &
    Technology, Shandong Jianzhu University, Jinan 250014, Shandong, China;
    4. School of Information Science and Electric Engineering, Shandong Jiaotong University, Jinan 250357, Shandong, China
  • Published:2019-03-19

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Abstract: There is a problem called class imbalance in many real-world datasets. When traditional classification algorithms classifying imbalanced data, it is easy to misclassify the minority class. In order to improve the classification accuracy of the samples from the minority class, this paper proposes a fixed-radius nearest neighbor progressive competition algorithm(FRNNPC). As a preconditioning, FRNNPC eliminates ineligible samples globally through the fixed-radius nearest neighbor rule, and use the NPC in the obtained candidate data to gradually calculate the score of the nearest neighbor sample of the query sample until the sum of the scores of the one class is higher than another class. In short, this method can effectively deal with the imbalance problem, and does not require any manually set parameters. The experimental results compare the proposed method with four representative algorithms applied to 10 imbalanced data sets, and illustrate the effectiveness of the algorithm.

Key words: imbalanced data, nearest neighbors rule, pattern classification

CLC Number: 

  • TP301.6
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