DocumentCode
1566680
Title
Research on Classifying Performance of SVM with Modified Kernel Function in HCCR
Author
Limin Sun ; Song, Yibin
Author_Institution
Sch. of Comput. Sci. & Technol., Yantai Univ.
Volume
3
fYear
2005
Firstpage
1720
Lastpage
1723
Abstract
Support vector machines theoretically show very good performance for two-group classification problem, and the performance largely depends on the kernel function. However, there are no theories concerning how to choose good kernel functions based on practical using problem. In this paper, we tried to modify kernel both in data-dependent and margin-dependent way and applied the method to offline handwritten Chinese character recognition to investigate its classifying performance. Our experiment results show that the performance is improved with the proposed algorithm
Keywords
handwritten character recognition; pattern classification; support vector machines; SVM modified kernel function; offline handwritten Chinese character recognition; support vector machines; two-group classification; Character recognition; Computer science; Electronic mail; Handwriting recognition; Kernel; Machine learning; Pattern recognition; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614960
Filename
1614960
Link To Document