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《Journal of Guangxi Normal University(Natural Science Edition)》 2016-01
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A kNN Classification Algorithm Based on Local Correlation

DENG Zhenyun;GONG Yonghong;SUN Ke;ZHANG Jilian;Guangxi Key Lab of Multi-source Information Mining & Security,Guangxi Normal University;Guilin University of Aerospace Technology;  
As a simple and effective classification algorithm,kNN algorithm is widely used in text classification.However,the k value(usually fixed)is usually set by users.For this purpose,the reconstruction and locality preserving projections(LPP)technology is introduced into the nearest neighbor classification,which makes the selection of the kvalue to be determined by the correlation between the samples and the topology structure.The algorithm uses l1-norm sparse coding method to reconstruct the test sample by its k(not fixed)nearest neighbor samples and LPP keeps the local structure of the sample after the reconstruction,which not only solves the problem of choosing kvalue,but also avoids the influence of fixed k value on classification.Experimental results show that the classification performance of the proposed method is better than that of the classical kNN algorithm.
【Fund】: 国家自然科学基金资助项目(61573270 61263035 61363009);; 国家973计划项目(2013CB329404);; 广西自然科学基金资助项目(2012GXNSFGA060004 2015GXNSFCB139011);; 中国博士后科学基金资助项目(2015M570837);; 广西多源信息挖掘与安全重点实验室开放基金资助项目(MIMS13-08)
【CateGory Index】: TP391.1
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