Regression on Power (NLL)
2.83NLLGP
Evaluation Results
| Method | Links | |
|---|---|---|
| GPExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=322026.07 | 2.83 | |
| BDKNExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 2.97 | |
| BLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.85 | |
| MFVIExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.88 | |
| VBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.97 | |
| LDBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 5.46 | |
| DEExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 6.89 | |
| DKLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 6.91 |