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http://dx.doi.org/10.7471/ikeee.2013.17.3.254

Active Selection of Label Data for Semi-Supervised Learning Algorithm  

Han, Ji-Ho (Dept. of Electronics Eng., Myong Ji University)
Park, Eun-Ae (Dept. of Electronics Eng., Myong Ji University)
Park, Dong-Chul (Dept. of Electronics Eng., Myong Ji University)
Lee, Yunsik (System IC R&D Division, KETI)
Min, Soo-Young (System IC R&D Division, KETI)
Publication Information
Journal of IKEEE / v.17, no.3, 2013 , pp. 254-259 More about this Journal
Abstract
The choice of labeled data in semi-supervised learning algorithm can result in effects on the performance of the resultant classifier. In order to select labeled data required for the training of a semi-supervised learning algorithm, VCNN(Vector Centroid Neural Network) is proposed in this paper. The proposed selection method of label data is evaluated on UCI dataset and caltech dataset. Experiments and results show that the proposed selection method outperforms conventional methods in terms of classification accuracy and minimum error rate.
Keywords
semi-supervised learning; label data; centroid neural network; data selection; classification;
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