document: Multi-output regression using a locally regularised orthogonal least-squares algorithm The paper considers data modelling using multi-output regression models . A locally regularised orthogonal least-squares -LRB- LROLS -RRB- 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 -LRB- OLS -RRB- model selection to produce a parsimonious model with a good generalisation performance is greatly enhanced
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