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Multi-output regression using a locally regularised orthogonal least-squares algorithm

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1 Author(s)
Chen, S. ; Dept. of Electron. & Comput. Sci., Southampton Univ., UK

The paper considers data modelling using multi-output regression models. A locally regularised orthogonal least-squares (LROLS) algorithm is proposed for constructing sparse multi-output regression models that generalise well. By associating each regressor in the regression model with an individual regularisation parameter, the ability of the multi-output orthogonal least-squares (OLS) model selection to produce a parsimonious model with a good generalisation performance is greatly enhanced

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Vision, Image and Signal Processing, IEE Proceedings -  (Volume:149 ,  Issue: 4 )