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Pattern Recognition and Artificial Intelligence  2022, Vol. 35 Issue (11): 989-998    DOI: 10.16451/j.cnki.issn1003-6059.202211004
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Near Neighborhood Classifier with Adaptive Radius Selection
ZHANG Qinghua1,2, XIAO Jiayu1,2, AI Zhihua2, WANG Guoyin1,2
1. Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065;
2. Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, Chongqing University of Posts and Telecommunications, Chongqing 400065

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Abstract  

In neighborhood rough sets, the neighborhood classifier is an intuitive and effective classification method in data mining. However, the neighborhood radius, as a key factor to determine the classification performance of the neighborhood classifier, has some defects in construction. The construction of the neighborhood radius is not universal due to the lack of the training stage. When the data samples are not uniformly distributed and then empty neighborhoods appear, the classifier fails. Aiming at these problems, a near neighborhood classifier with adaptive radius selection(NNC-AR) is proposed. Firstly, for training samples, a training neighborhood radius based on K-nearest neighbor is defined. For test samples, an adaptive neighborhood radius is defined to overcome the subjectivity of the artificial parameter in the traditional neighborhood radius. Finally, for the test samples with classifier failure, an approximate neighborhood radius is defined to improve the generalization ability of the classifier. The experimental results show that the F1 score and classification accuracy of NNC-AR model are significantly improved.

Key wordsKey Words Neighborhood Rough Set      Neighborhood Classifier      Neighborhood Radius      Adaptive Radius     
Received: 29 September 2022     
ZTFLH: TP 18  
Fund:

National Key Research and Development Program of China(No.2020YFC2003502), National Natural Science Foundation of China (No.62276038)

Corresponding Authors: ZHANG Qinghua, Ph.D., professor. His research interests include rough sets, fuzzy sets, granular computing and three-way decision-making.   
About author:: XIAO Jiayu, master student. Her research interests include intelligent information processing and data mining. AI Zhihua, master student. His research interests include intelligent information processing and data mining. WANG Guoyin, Ph.D., professor. His research interests include rough sets, granular computing, cognitive computing, data mining and intelligent information processing.
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ZHANG Qinghua
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Cite this article:   
ZHANG Qinghua,XIAO Jiayu,AI Zhihua等. Near Neighborhood Classifier with Adaptive Radius Selection[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(11): 989-998.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202211004      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I11/989
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