FAST M-TLS-RSVR AND M-LS-e-TSVR FOR MULTI-OUTPUT REGRESSION
Chunhui Zhao, Liya Fan · International Journal of Applied Mathematics and Machine Learning · 2017
This paper focuses on research multi-output regression problems and proposes two novel fast learning algorithms named as fast multi-output twin least squares regularized SVR (FM-TLS-RSVR) and fast multi-output least squares ( ), TSVR --LS -FM TSVR -ε ε respectively.The main advantage of the proposed methods is to consider the cross relations among output vectors as a whole and avoid the singularity of matrices.In addition, the proposed FM-TLS-RSVR also possesses the sparsity.Experiment results indicate that FM-TLS-RSVR and TSVR --LS -FM ε are two effective and competitive multi-output regressors.