DocumentCode
2591538
Title
Applied research in iatrology classification based on SVM
Author
Bi, Li
Author_Institution
Sch. of Math. & Comput., Ningxia Univ., Yinchuan, China
Volume
4
fYear
2011
fDate
15-17 Oct. 2011
Firstpage
2049
Lastpage
2053
Abstract
In the paper we introduced the soft margin SVC to solve linearly inseparable problems. Compared with the kernel trick, it is obvious that the two approaches actually solve the problems in different manners. Then we provided a novel view to design a kernel function based on a general proximity relation mapping. It shows better classification performance than the common Mercer kernels experimentally in the iatrology area.
Keywords
biomedical engineering; data mining; medical computing; pattern classification; support vector machines; SVM based iatrology classification; general proximity relation mapping; kernel function; linearly inseparable problems; soft margin SVC; Classification algorithms; Equations; Kernel; Static VAr compensators; Support vector machines; Training; Vectors; SVM(Support vector machines); classifier; data mining algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-9351-7
Type
conf
DOI
10.1109/BMEI.2011.6098738
Filename
6098738
Link To Document