A Fast and Efficient Algorithm for Border Extraction

Author

Lin, Zhi-Yong ; Hao, Zhi-Feng ; Yang, Xiao-Wei

Author_Institution

South China Univ. of Technol., Guangzhou

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3302

Lastpage

3307

Abstract

For some classification methods, such as support vector machine, the border examples are useful in the classifier design. In this paper, a fast algorithm for border extraction is proposed. The algorithm is firstly derived from the linearly separated case intuitively. Then, through kernel trick, the algorithm is extended to the nonlinearly separated case. Several simulations are carried out to evaluate the algorithm´s performance, and the results show its effectiveness. Also, the effects of the parameters on the algorithm are discussed, and some suggestions on how to select the parameters are presented.

Keywords

feature extraction; pattern classification; support vector machines; border extraction; classification methods; classifier design; kernel function; kernel trick; pattern classification; support vector machine; Cellular neural networks; Computer science; Data mining; Kernel; Nearest neighbor searches; Neural networks; Prototypes; Supervised learning; Support vector machine classification; Support vector machines; Border extraction; Kernel function; Pattern classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370718

Filename

4370718