Table 3 Differences in best hyperparameter selection for different folding methods on the public data set. The top 10 performing hyperparameter sets for the random fold splitting are given together with the respective rank of this setting for the other folding methods
From: Splitting chemical structure data sets for federated privacy-preserving machine learning
Hidden | Dropout | Weight | Rank | Rank | Rank |
|---|---|---|---|---|---|
Sizes | Â | Decay | Sphere exclusion | Scaffold network | LSH |
[2000] | 0.7 | 1E−6 | 2 | 1 | 8 |
[2000] | 0.6 | 1E−6 | 8 | 6 | 5 |
[1600] | 0.7 | 1E−6 | 3 | 2 | 2 |
[1200] | 0.5 | 1E−6 | 11 | 13 | 7 |
[1200] | 0.6 | 1E−6 | 9 | 10 | 4 |
[3000] | 0.7 | 1E−6 | 5 | 4 | 6 |
[1200] | 0.7 | 1E−6 | 1 | 3 | 1 |
[1600] | 0.6 | 1E−6 | 6 | 9 | 3 |
[3000] | 0.6 | 1E−6 | 7 | 8 | 11 |
[1600] | 0.5 | 1E-6 | 4 | 11 | 10 |