Figure 5. Effect of acceleration parameter on the training and testing error for four different data sets and two different MediBoost algorithms (MAB and LMB).

In all cases, the training error decreases as the acceleration parameter increases (accelerating the convergence of the algorithm) while the testing error improves or remains the same.