International Journal of Applied Mathematics and Machine LearningAuthor's: Min Hou and Liya Fan
Pages: [1] - [14]
Received Date: December 27, 2016
Submitted by: Jianqiang Gao.
DOI: http://dx.doi.org/10.18642/ijamml_7100121755
In order to improve the regression accuracy of MLS-SVR presented by Xu et al. [10] with a fast training algorithm, this paper proposes a new regression method named as multi-output least squares twin SVR (MLS-TSVR) for multi-output problems. The main advantage of the proposed method is that the relations among output weight vectors are considered as a whole rather than decomposed in MLS-SVR. Experimental results show that MLS-TSVR has a good property on regression accuracy.
multi-output regression problem, least-squares technique, twin support vector regression machine, regression accuracy.
