Abstract
Semi-supervised learning has become an active area of recent research in machine learning. To date,many approaches to semi-supervised learning are presented. In this paper,Consistency method and its some variants are deeply studied. The proof about the important condition for convergence of consistency method is given in detail. Moreover,we further study the validity of some variants of consistency method. Finally we conduct the experimental study on the parameters involved in consistency method to face recognition. Meanwhile, the performance of Consistency method and its some variants are compared with that of support vector machine supervised learning methods.
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Li, K., Yang, N., Ye, X. (2010). Face Recognition Using Consistency Method and Its Variants. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_63
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DOI: https://doi.org/10.1007/978-3-642-16248-0_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16247-3
Online ISBN: 978-3-642-16248-0
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