DocumentCode
2005698
Title
Rank Space Diversity: A Diversity Measure of Base Kernel Matrices
Author
Luo, Linkai ; Lin, Chengde ; Peng, Hong ; Zhou, Qifeng
Author_Institution
Xiamen Univ., Xiamen
fYear
2007
fDate
May 30 2007-June 1 2007
Firstpage
1594
Lastpage
1599
Abstract
This paper studies the diversity measure of base kernel matrices. First, rank space diversity is proposed as a diversity measure of base kernel matrices. Then, a rule for choosing base kernel matrices is deduced by this diversity measure. Last, our rule´s validation is claimed by some experiments on artificial data set and benchmark data set.
Keywords
learning (artificial intelligence); matrix algebra; base kernel matrices; diversity measure; rank space diversity; Automatic control; Automation; Data mining; Extraterrestrial measurements; Kernel; Machine learning; Matrices; Support vector machines; Testing; Training data; diversity measure of base kernel matrices; learning kernel matrices; rank space diversity;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-0818-4
Electronic_ISBN
978-1-4244-0818-4
Type
conf
DOI
10.1109/ICCA.2007.4376629
Filename
4376629
Link To Document