Figure shows a visualization of chemical space computed with t-Distributed Stochastic Neighbor Embedding (t-SNE). This is a dimensionality reduction technique Analysis of variance (ANOVA) was performed in these sets and shows a significant difference overall between the 3 properties (p=2.2 × 10 -13 ). However, this does not tell us what those differences are. Using Tukey's honestly significantly differenced test, which compares each group which each other, we see that polarizability has a significantly different set of Tanimoto coefficients than optical bandgap (p<=0.001) or solvation energy ratio (p<=0.001). This indicates that among the three properties, polarizability has a more localized search space of top performers, while the other target properties are more diverse. Examining the GA performance across all three parameters will give generalized hyperparameters that can work on future chemical properties, regardless of chemical space diversity.