Regression on Sulfur (RMSE)
0.34RMSEDTSemNet Top-k
Evaluation Results
| Method | Links | |
|---|---|---|
| DTSemNet Top-kHeight=5, Number of features (Nf)=6, Number of training samples (Ns)=70562026.05 | 0.34 | |
| DTSemNet STEHeight=5, Number of features (Nf)=6, Number of training samples (Ns)=70562026.05 | 0.35 | |
| DGT-LinearHeight=5, Number of features (Nf)=6, Number of training samples (Ns)=70562026.05 | 0.35 | |
| CARTNumber of features (Nf)=6, Number of training samples (Ns)=70562026.05 | 0.43 |