Study of implicit information semi-supervised learning algorithm

Autor:	Guo-dong LIU, Jing XU, Guo-bing ZHANG
Jazyk:	čínština
Rok vydání:	2015
Předmět:	semi-supervised learning lung sounds implicit information Telecommunication TK5101-6720
Zdroj:	Tongxin xuebao, Vol 36, Pp 133-139 (2015)
Druh dokumentu:	article
ISSN:	1000-436X 26104725
DOI:	10.11959/j.issn.1000-436x.2015263
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/855ca74b261047258eac59681a91838b Zobrazit plný text záznamu View record in DOAJ