Regression on ELEVATORS
0.2RMSEDTSemNet Top-k
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| DTSemNet Top-kHeight=4, Number of features (Nf)=16, Number of training samples (Ns)=116192026.05 | 0.2 | — | — | — | |
| DTSemNet STEHeight=4, Number of features (Nf)=16, Number of training samples (Ns)=116192026.05 | 0.21 | — | — | — | |
| DGT-LinearHeight=4, Number of features (Nf)=16, Number of training samples (Ns)=116192026.05 | 0.21 | — | — | — | |
| CGNoise Level=Standard2023.06 | 0.35 | — | 1.72 | 0.38 | |
| SVGPNoise Level=Standard2023.06 | 0.37 | — | 21.3 | 0.43 | |
| SGD-GPNoise Level=Standard2023.06 | 0.38 | — | 3.51 | 0.47 | |
| CARTNumber of features (Nf)=16, Number of training samples (Ns)=116192026.05 | 0.54 | — | — | — | |
| CGNoise Level=Low2023.06 | — | 0.68 | — | — | |
| SGD-GPNoise Level=Low2023.06 | — | 0.38 | — | — |