Table 3.

RMSE and standard error of the predictions. The entries in bold denote the best performing model(s).

Dataset	BLR	VI	FedAG${}_{\mathit{N}=0}^{(\mathit{t}=1)}$	FedAG${}_{\mathit{N}=1}^{(\mathit{t}=5)}$	DE
Boston	$4.87\pm 0.22$	$\mathbf{4.32}\pm \mathbf{0.29}$	$4.96\pm 0.22$	$\mathbf{4.07}\pm \mathbf{0.18}$	$\mathbf{3.28}\pm \mathbf{1.00}$
Concrete	$10.58\pm 0.33$	$7.13\pm 0.12$	$10.52\pm 0.33$	$\mathbf{6.50}\pm \mathbf{0.20}$	$\mathbf{6.03}\pm \mathbf{0.58}$
Energy	$4.35\pm 0.14$	$2.65\pm 0.08$	$4.36\pm 0.14$	$\mathbf{2.02}\pm \mathbf{0.07}$	$\mathbf{2.09}\pm \mathbf{0.29}$
Kin8nm	$0.20\pm 0.00$	$0.10\pm 0.00$	$0.20\pm 0.00$	$0.10\pm 0.00$	$\mathbf{0.09}\pm \mathbf{0.00}$
Naval Propulsion	$0.01\pm 0.00$	$\mathbf{0.00}\pm \mathbf{0.00}$	$0.01\pm 0.00$	$0.01\pm 0.00$	$\mathbf{0.00}\pm \mathbf{0.00}$
Power Plant	$4.74\pm 0.05$	$4.33\pm 0.04$	$4.56\pm 0.05$	$4.45\pm 0.05$	$\mathbf{4.11}\pm \mathbf{0.17}$
Protein	$5.18\pm 0.02$	$4.84\pm 0.03$	$5.18\pm 0.02$	$\mathbf{4.63}\pm \mathbf{0.02}$	$\mathbf{4.71}\pm \mathbf{0.06}$
Red Wine	$\mathbf{0.65}\pm \mathbf{0.02}$	$\mathbf{0.65}\pm \mathbf{0.01}$	$\mathbf{0.65}\pm \mathbf{0.02}$	$\mathbf{0.65}\pm \mathbf{0.02}$	$\mathbf{0.64}\pm \mathbf{0.04}$
Yacht	$9.12\pm 0.52$	$6.89\pm 0.67$	$9.12\pm 0.52$	$2.29\pm 0.15$	$\mathbf{1.58}\pm \mathbf{0.48}$
Year Prediction	$9.51\pm \mathrm{NA}$	$9.03\pm \mathrm{NA}$	$9.51\pm \mathrm{NA}$	$9.35\pm \mathrm{NA}$	$\mathbf{8.89}\pm \mathbf{NA}$