Once the clusters are established we randomly added a cluster to either the Training, Withheld, or Testing set. Due to our Training and Testing sets sizes being predefined for our active learning scheme, we only added a cluster to a given set if the set had enough remaining space to contain the cluster. This process was repeated with 5 different random seeds to create the "CCV" dataset. We then created the "Largest Cluster" dataset by randomly splitting the largest cluster into a Training, Withheld, and Testing set and storing the remaining clusters in the External set. Again, this process was repeated 5 times with different random seeds. This same procedure was performed with the largest and third largest clusters to create the "Clusters 02" dataset. Lastly, we created the "Largest Cluster Validation" set by copying the corresponding fold of the "Largest Cluster" set's Training and Testing sets, and then then randomly selecting 50 molecules from the prior Withheld set to use as a new External set (leaving the remaining molecules as the Withheld set). This allows our models in Experiment 8 to be fit with respect to a subset of molecules within cluster (Test set) and evaluated on a different set of molecules also within cluster (new External set). The sizes of each dataset are described in Table . Additionally, a PCA visualization of the largest cluster and the secondary cluster we selected for improved coverage in later experiments is shown in Figure .