Table 1 Performance evaluation of the multi-task learning (MTL) methods (including the MTL-SGL, ℓ_{1, 2} MTL and ℓ_{1, ∞} MTL), and the single task learning methods (including Lasso regression and sparse group lasso regression). The rooted mean square error (RMSE), Average accuracy (Acc.), Average sensitivity (Sen.), Average specificity (Spe.), Area Under Receiver Operating Characteristic Curves (AUC), and Area Under Precision-Recall Curves (AUPR) were evaluated. Bold indicates the best performance

From: Multi-task learning sparse group lasso: a method for quantifying antigenicity of influenza A(H1N1) virus using mutations and variations in glycosylation of Hemagglutinin