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Interactive support vector machine learning algorithm and its application

LU Zengxiang, LI Yanda Department of Automation, Tsinghua University, Beijing 100084, China  
Interactive support vector machine (SVM) can solve some supervised learning problems which are lack of learning samples. The algorithm bases on SVM. An interactive process is introduced in classifier's design. According to the prior SVM classifier, an “useful” sample can be select actively, then you can get the better SVM calssifier. Comparing with the general SVM, it greatly reduces the number of samples, and probably reaches higher generalization ability. The application on text information filtering shows a successful example using this algorithm.
【Fund】: 国家教委“211”工程项目
【CateGory Index】: TP301
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