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ResearchFormerly WizWand

Quantile Regression on Scenario 3 n=5000

0.8839MSE (τ=0.05)ConquerNet
0.86670.98281.09891.215May 7, 2026
Updated 6mo ago

Evaluation results

MethodLinks
ConquerNetModel=Model B, Kernel=Epanechnikov2026.050.88390.32620.21120.32110.9264
ConquerNetModel=Model B, Kernel=Uniform2026.050.94310.33940.2002—0.8535
BaselineModel=Model B2026.050.98130.3330.21480.31460.9632
ConquerNetModel=Model B, Kernel=Gaussian2026.050.99650.31960.2130.30270.8176
ConquerNetModel=Model B, Smoothing Kernel=Epanechnikov2026.051.00530.3750.22970.3473—
BaselineModel=Model B2026.051.00610.35960.21960.35511.099
ConquerNetModel=Model B, Smoothing Kernel=Gaussian2026.051.06020.42630.23040.35251.0681
ConquerNetModel=Model A, Kernel=Uniform2026.051.11470.35210.21040.30961.117
ConquerNetModel=Model A, Kernel=Gaussian2026.051.12220.33390.21430.30450.9996
ConquerNetModel=Model A, Smoothing Kernel=Epanechnikov2026.051.12290.36150.1980.31121.3312
ConquerNetModel=Model A, Smoothing Kernel=Uniform2026.051.15770.34490.19120.30821.2392
BaselineModel=Model A2026.051.18720.37410.22980.36261.1419
ConquerNetModel=Model B, Smoothing Kernel=Uniform2026.051.20560.40380.2320.33731.0528
ConquerNetModel=Model A, Kernel=Epanechnikov2026.051.24440.3520.21450.32471.2093
BaselineModel=Model A2026.051.2870.38540.21460.33871.3495
ConquerNetModel=Model A, Smoothing Kernel=Gaussian2026.051.31390.33790.19930.32691.1897