DocumentCode :
2560709
Title :
An introduction interval kernel-Based methods applied on Support Vector Machines
Author :
Takahashi, Adriana ; Dória Neto, Adrião D. ; Bedregal, Benjamín R C
Author_Institution :
Fed. Univ. of Rio Grande do Norte, Natal, Brazil
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
58
Lastpage :
64
Abstract :
In this work we propose a generalized real interval kernel method applied on Support Vector Machines. Since the real interval kernel method is constructed from the real kernel method, it is reasonable to extend it to intervals on any domain which has some algebraic structure. This extension is applied on Support Vector Machines classification of interval data.
Keywords :
digital arithmetic; pattern classification; support vector machines; SVM; algebraic structure; data classification; interval kernel method; support vector machine; Buildings; Eigenvalues and eigenfunctions; Equations; Kernel; Support vector machines; Symmetric matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234756
Filename :
6234756
Link To Document :
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