International Journal of Applied Mathematics and Machine Learning
FOR MULTI-OUTPUT REGRESSION[1] Ning Wang, Min Han Nuo Dong and Meng Joo Er, Constructive
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[2] Pan Tian, Jie Hu, Jin Qi, Peng Xia and Ying-Hong Peng, Application
of multi-output support vector regression on EMGs to decode hand
continuous movement trajectory, Bio-Medical Materials and Engineering
26 (2015), 575-582.
[3] N. Cristianini and J. Shawe-Taylor, An Introduction to Support
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[4] F. Prez-Cruz, G. Camps-Valls, E. Soria-Olivas et al.,
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[5] Wentao Mao, Jiucheng Xu, Chuan Wang and Longlei Dong, A fast and
robust model selection algorithm for multi-input multi-output support
vector machine, Neurocomputing 130 (2014), 10-19.
[6] Li Zhang, Wei-Da Zhou, Pei-Chann Chang, Ji-Wen Yang and Fan-Zhang
Li, Iterated time series prediction with multiple support vector
regression models, Neurocomputing 99 (2013), 411-422.
[7] Yongping Zhao, Jing Zhao and Min Zhao, Twin least squares support
vector regression, Neurocomputing 118 (2013), 225-236.
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support vector machine for regressor,
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[10] S. Xu, X. An, X. Xiao, L. Zhu and L. Li, Multi-output
least-squares support vector regression machines, Pattern Recognition
Letters 34 (2013), 1078-1084.
