List your company
ResearchFormerly WizWand

Quantile Regression on Scenario 2 n=1000

0.4515MSE (τ=0.05)ConquerNet
0.4327920.5590710.685350.811629May 7, 2026
Updated 6mo ago

Evaluation results

MethodLinks
ConquerNetModel=Model B, Smoothing Kernel=Uniform2026.050.45150.07170.05030.09350.6034
BaselineModel=Model B2026.050.4930.05830.04930.0840.5898
BaselineModel=Model B2026.050.5210.06830.06510.08690.7145
ConquerNetModel=Model B, Smoothing Kernel=Epanechnikov2026.050.580.07230.05460.08190.7484
ConquerNetModel=Model B, Kernel=Epanechnikov2026.050.64140.08790.0580.08680.5577
ConquerNetModel=Model B, Kernel=Uniform2026.050.6440.06050.05230.08080.5217
ConquerNetModel=Model A, Kernel=Epanechnikov2026.050.68870.08270.07160.11850.6827
ConquerNetModel=Model B, Kernel=Gaussian2026.050.71540.070.05530.08270.5483
ConquerNetModel=Model B, Smoothing Kernel=Gaussian2026.050.73670.06390.050.07590.6273
ConquerNetModel=Model A, Kernel=Gaussian2026.050.74810.07040.05770.09060.7275
BaselineModel=Model A2026.050.78920.08010.06550.10170.7819
ConquerNetModel=Model A, Smoothing Kernel=Gaussian2026.050.79940.07110.05870.07781.1466
ConquerNetModel=Model A, Kernel=Uniform2026.050.8190.07340.06470.10530.889
BaselineModel=Model A2026.050.82920.08680.06190.08390.7874
ConquerNetModel=Model A, Smoothing Kernel=Uniform2026.050.88920.07210.04710.09640.8566
ConquerNetModel=Model A, Smoothing Kernel=Epanechnikov2026.050.91920.07870.05220.10480.9074