DocumentCode
1749836
Title
A new optimizing procedure for ν-support vector regressor
Author
Perez-Cruz, Fernando ; Artes-Rodriguez, Antonio
Author_Institution
Dpto. Teoria de la Senal y Comunicaciones, Univ. de Alcala, Madrid, Spain
Volume
2
fYear
2001
fDate
2001
Firstpage
1265
Abstract
We present an approach to solve the v-SVR. It is based on an iterative re-weighted least squares (IRWLS) procedure, which is simple to implement and can be tuned to the usual ν-SVR solution. The IRWLS procedure is much more efficient (computational load) than quadratic programming techniques, which are usually employed to solve it
Keywords
Hilbert spaces; learning automata; least squares approximations; optimisation; statistical analysis; ν-support vector regressor; computational load; iterative re-weighted least squares; optimizing procedure; support vector machine; Computational complexity; Lagrangian functions; Least squares methods; Quadratic programming; Signal processing; Signal processing algorithms; Static VAr compensators; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location
Salt Lake City, UT
ISSN
1520-6149
Print_ISBN
0-7803-7041-4
Type
conf
DOI
10.1109/ICASSP.2001.941155
Filename
941155
Link To Document