Quantile Regression on Scenario 1 (n=5000)
0.0996MSE (Quantile 0.05)Baseline
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| BaselineModel=Model A2026.05 | 0.0996 | 0.012 | 0.0086 | 0.0108 | 0.0939 | |
| ConquerNetModel=Model A, Kernel=Gaussian2026.05 | 0.1006 | 0.0249 | 0.0118 | 0.009 | 0.0889 | |
| ConquerNetModel=Model B, Smoothing Kernel=Uniform2026.05 | 0.1033 | 0.0145 | 0.0091 | 0.0154 | 0.1252 | |
| BaselineModel=Model A2026.05 | 0.1051 | 0.0221 | 0.012 | 0.0121 | 0.0797 | |
| ConquerNetModel=Model A, Smoothing Kernel=Uniform2026.05 | 0.1079 | 0.0087 | 0.0059 | 0.0104 | 0.1312 | |
| ConquerNetModel=Model B, Smoothing Kernel=Epanechnikov2026.05 | 0.1115 | 0.0146 | 0.0094 | 0.0145 | 0.1162 | |
| ConquerNetModel=Model A, Smoothing Kernel=Gaussian2026.05 | 0.1124 | 0.0087 | 0.0055 | 0.0097 | 0.1081 | |
| ConquerNetModel=Model A, Kernel=Uniform2026.05 | 0.1139 | 0.0255 | 0.0113 | 0.0092 | 0.0881 | |
| BaselineModel=Model B2026.05 | 0.1143 | 0.0149 | 0.0107 | 0.0151 | 0.1277 | |
| ConquerNetModel=Model A, Kernel=Epanechnikov2026.05 | 0.1149 | 0.0259 | 0.0115 | 0.009 | 0.0928 | |
| ConquerNetModel=Model B, Smoothing Kernel=Gaussian2026.05 | 0.1172 | 0.0144 | 0.0097 | 0.0142 | 0.1066 | |
| ConquerNetModel=Model B, Kernel=Uniform2026.05 | 0.124 | 0.0389 | 0.0196 | 0.0137 | 0.0698 | |
| BaselineModel=Model B2026.05 | 0.1249 | 0.0293 | 0.0191 | 0.0162 | 0.062 | |
| ConquerNetModel=Model A, Smoothing Kernel=Epanechnikov2026.05 | 0.1251 | 0.0093 | 0.0055 | 0.0095 | 0.1169 | |
| ConquerNetModel=Model B, Kernel=Epanechnikov2026.05 | 0.1272 | 0.0379 | 0.019 | 0.0131 | 0.0669 | |
| ConquerNetModel=Model B, Kernel=Gaussian2026.05 | 0.136 | 0.0386 | 0.0187 | 0.0131 | 0.0709 |