Study of implicit information semi-supervised learning algorithm

被引：0

作者：

Liu, Guo-Dong ^{[1
]}

Xu, Jing ^{[1
]}

Zhang, Guo-Bing ^{[2
]}

机构：

[1] College of Computer and Control Engineering, Nankai University, Tianjin,300071, China

[2] School of Electronic and Information Engineering, Beihang University, Beijing,100191, China

来源：

Tongxin Xuebao/Journal on Communications | 2015年 / 36卷 / 10期

关键词：

Support vector machines - Decision trees - Biological organs;

D O I：

10.11959/j.issn.1000-436x.2015263

中图分类号：

学科分类号：

摘要：

Implicit information semi supervised learning algorithm was studied. The implicit information semi supervised learning algorithm was used in support vector machine and random forest, which were called semi-SVM and semi-RF. The semi-SVM and semi-RF were evaluated by using UCI, the experimental results show that the semi-SVM and semi-RF are more effective and more precise. The semi-SVM and semi-RF were applied to classifying lung sounds, and verified the effect by using the actual lung sounds data. the quantity and quality of samples affect semi-SVM and semi-RF were analyzed. ©, 2015, Editorial Board of Journal on Communications. All right reserved.

引用

页码：133 / 139

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