By comparing extremes such as having no chemical information, but a larger initialization set (Figure , OHE 20) to using a smaller fully parametrized initialization dataset (Full features 10), the effects of parametrization complexity and initialization data size could be more clearly identified. Within the case study, the results clearly indicated that having a dataset parameterized to higher complexity only delivers acceptable learning curves when the size of the initial dataset is sufficiently large. When using 10 datapoints for initialization, the OHE dataset clearly outperformed the fully parameterized dataset, however, when using 20 datapoints for initialization we found less of a difference in performance. When comparing size of the initial dataset against complexity of parameterization, we found that OHE 20