An Optimized Method for Semi-supervised Support Vector Machines
In view of problem of non-convex optimization problem that semi-supervised support vector machines use margin maximization principle to classify labeled and unlabeled samples, a method EDA_S3VM was proposed which using estimation of distribution algorithm to optimize semi-supervised support vector m...
Main Authors: | WANG Yong, CHENG Can, DAI Ming-jun, SUN Yong |
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Format: | Article |
Language: | zho |
Published: |
Editorial Department of Industry and Mine Automation
2010-12-01
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Series: | Gong-kuang zidonghua |
Subjects: | |
Online Access: | http://www.gkzdh.cn/article/id/2025 |
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