The middle right panel of Fig. shows how variance error decreases with the dataset size as well. The slope of decrease is steeper with bias error than with variance error. This dynamic gives rise to the changing proportion of error attributable to bias (top right panel). At small dataset sizes, the error is dominated by bias errors with only a small fraction due to variance. As the dataset size increases, both bias and variance error decrease but the proportion of error steadily becomes dominated by the variance error. The bottom panels of Fig. depicts the total error for hidden sizes of 2000 (left) and 20 (right) decomposed into variance (dashed line) and bias (dotted line), showing the transition from bias dominated error to variance dominated error clearly in the two extreme model size cases.