DocumentCode
2775292
Title
A Novel Semi-Supervised Learning Methods Using Support Vector Domain Description
Author
Lee, Daewon ; Lee, Jaewook
Author_Institution
Pohang Univ. of Sci. & Technol., Pohang
fYear
0
fDate
0-0 0
Firstpage
3627
Lastpage
3633
Abstract
A new learning algorithm for semi-supervised learning is proposed. The proposed method utilizes a support vector machine to describe domains and a dynamical system to decompose the data space into several labelled disjoint regions. It can classify unlabelled data and predict new unknown data. Effectiveness of the method is verified through simulation results.
Keywords
learning (artificial intelligence); support vector machines; dynamical system; semisupervised learning method; support vector machine; Bioinformatics; Humans; Kernel; Machine learning; Semisupervised learning; Space technology; Supervised learning; Support vector machine classification; Support vector machines; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.247375
Filename
1716597
Link To Document