Figure 8.

Histograms highlighting the distribution of standard deviations of the model continuous score (top) and model predicted class (bottom) at the image level across 20 runs, for each of two representative models, where (a) model # 36 and (b) model # 77. For both models (a) and (b), model predictions are derived from “Model Selection Set”/“Test Set 1” (left) and “Test Set 2” (right) respectively. These results indicate that model predictions are consistent across repeat runs, within each model configuration and test set; this is highlighted by the large density of standard deviations of the model predicted class at the image level near 0 (meaning that for a given model configuration, the predicted class of an image remains relatively constant across repeat runs) and the small maximum standard deviation around 0.08 – 0.1 (meaning that the model predicted continuous score of an image also changes minimally across repeat runs, and certainly not enough to propagate to a resulting change in predicted class).