Figure 3: Two-step prediction pipeline design.

The box plots in (A) show the distribution of classification probability values for infants assigned by the model to the correct median score group. Since the variability of the underlying data distribution is small this translates to a very large learning step as seen by the red lines in (B), which in turn may be difficult for a single model design. Alternatively, by introducing a second model building step, which normalizes the classification probabilities, the large learning step is transformed to a smaller learning step as seen by the green lines in (B). As a result, a two-step prediction pipeline design approach may better identify subtle correlations between white matter connectomes and cognitive ability