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《Journal of University of Science and Technology Liaoning》 2010-05
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Application of SVM-KNN classifier on abnormal behavior detection

LIN Chun-li1,2,QI Xin3,WANG Ke-cheng3(1.College of Automation,Harbin Engineering University,Harbin 150001,China;2.School of Higher Vocational Education,University of Science and Technology Liaoning,Anshan 114051,China;3.School of Electric and Information Engineering,University of Science and Technology Liaoning,Anshan 114051,China)  
An abnormal behavior detection method is proposed by combining SVM algorithm with KNN algorithm.During the preprocessing phase,when the distance from the test samples to the optimal hyper plane is greater than the given threshold,SVM algorithm is applied to classify test samples,otherwise KNN algorithm would be used to reduce the misclassification probability.Results of experiments show this method of SVM-KNN algorithm has gained the accuracy of 95.86% on abnormal behavior detection.
【CateGory Index】: TP18
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