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ResearchFormerly WizWand

Quantile Regression on Scenario 3 n=1000

1.9425MSE (τ=0.05)ConquerNet
1.8640042.3938522.92373.453548May 7, 2026
Updated 6mo ago

Evaluation results

MethodLinks
ConquerNetModel=Model B, Kernel=Uniform2026.051.94250.81810.48240.76441.9375
ConquerNetModel=Model B, Smoothing Kernel=Uniform2026.052.19460.83160.51930.73522.5765
BaselineModel=Model B2026.052.25660.78010.50420.74462.277
ConquerNetModel=Model B, Smoothing Kernel=Gaussian2026.052.31930.84050.51420.75432.652
ConquerNetModel=Model B, Kernel=Epanechnikov2026.052.4130.78070.54030.73331.9167
ConquerNetModel=Model B, Kernel=Gaussian2026.052.54810.75690.53220.82492.0108
BaselineModel=Model B2026.052.81660.75580.51750.76652.2839
ConquerNetModel=Model A, Kernel=Gaussian2026.052.85430.95410.58280.77022.7395
ConquerNetModel=Model A, Smoothing Kernel=Gaussian2026.052.88410.77760.47880.70563.4222
ConquerNetModel=Model B, Smoothing Kernel=Epanechnikov2026.052.97020.90080.48920.87022.1331
ConquerNetModel=Model A, Kernel=Epanechnikov2026.053.04670.81310.56380.76062.6823
BaselineModel=Model A2026.053.07660.75640.5350.74072.8969
BaselineModel=Model A2026.053.17290.8820.55870.84563.0478
ConquerNetModel=Model A, Smoothing Kernel=Uniform2026.053.3730.77350.48760.78323.3576
ConquerNetModel=Model A, Smoothing Kernel=Epanechnikov2026.053.44790.73080.46790.81533.3156
ConquerNetModel=Model A, Kernel=Uniform2026.053.90490.83990.56650.74722.842