Touch Pointing Parameter Estimation on Experiment 3 Full Aggregate Data (train)
0.991R2Random Forest
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Random ForestFormula=SR, Hyperparameter Optimization=default, number of parameters=28,3122026.03 | 0.991 | 0.979 | 1.28 | 1.43 | |
| Random ForestFormula=SR, Hyperparameter Optimization=Bayesian-optimized, number of parameters=49,2172026.03 | 0.982 | 1.39 | 1.82 | 2.07 | |
| SVRFormula=SR, Hyperparameter Optimization=Bayesian-optimized, number of parameters=1812026.03 | 0.973 | 1.57 | 2.26 | 2.31 | |
| MLP Neural NetFormula=SR, Hyperparameter Optimization=Bayesian-optimized, number of parameters=41,4012026.03 | 0.96 | 2.19 | 2.73 | 3.11 | |
| Skewed-Dual.Formula=SRx (Equation 11)2026.03 | 0.917 | 2.6 | 3.46 | 3.18 | |
| Skewed-Dual.Formula=SR (Equation 6)2026.03 | 0.888 | 3.52 | 4.57 | 4.92 | |
| Skewed-Dual.Formula=SRy (Equation 11)2026.03 | 0.881 | 2.76 | 3.65 | 3.34 | |
| Dual Gauss.Formula=SRy (Equation 4)2026.03 | 0.865 | 2.8 | 3.9 | 3.42 | |
| Skewed-Dual.Formula=γ1x (Equation 16), Regression Constants=cx = 2.48, dx = −0.3702026.03 | 0.806 | 0.272 | 0.363 | 63.5 | |
| Lasso RegressionFormula=SR, Hyperparameter Optimization=Bayesian-optimized, number of parameters=52026.03 | 0.798 | 4.9 | 6.13 | 7.07 | |
| Lasso RegressionFormula=SR, Hyperparameter Optimization=default, number of parameters=52026.03 | 0.795 | 4.93 | 6.19 | 7.15 | |
| Dual Gauss.Formula=SR (Equation 5)2026.03 | 0.784 | 4.71 | 6.35 | 6.64 | |
| Dual Gauss.Formula=SRx (Equation 4)2026.03 | 0.75 | 4.36 | 6.01 | 5.48 | |
| Skewed-Dual.Formula=µx (Equation 18), Regression Constants=jx = 0.560, kx = −0.0548, lx = 6.202026.03 | 0.73 | 0.179 | 0.232 | 133 | |
| Skewed-Dual.Formula=σx (Equation 17), Regression Constants=ex = 1.42, fx = 0.0249, gx = 0.295, hx = 2.69, ix = 0.01282026.03 | 0.679 | 0.093 | 0.114 | 5.64 | |
| SVRFormula=SR, Hyperparameter Optimization=default, number of parameters=2252026.03 | 0.663 | 6.56 | 7.93 | 10 | |
| Skewed-Dual.Formula=γ1y (Equation 16 using Dedge y), Regression Constants=cy = 1.16, dy = −0.2102026.03 | 0.417 | 0.278 | 0.363 | 124 | |
| Dual Gauss.Formula=σ2x (Equation 1), Regression Constants=ax = 0.0175, bx = 2.302026.03 | 0.314 | 0.441 | 0.543 | 17.7 | |
| Skewed-Dual.Formula=σy (Equation 17 using H & Marginy), Regression Constants=ey = 2.07, fy = 0.00304, gy = −0.0299, hy = 2.38, iy = 0.01272026.03 | 0.305 | 0.14 | 0.183 | 8.7 | |
| Skewed-Dual.Formula=µy (Equation 18 using Dedge y), Regression Constants=jy = 0.408, ky = 0.0158, ly = 5.862026.03 | 0.226 | 0.144 | 0.177 | 42.4 | |
| Dual Gauss.Formula=σ2y (Equation 1), Regression Constants=ay = 0.0107, by = 2.152026.03 | 0.089 | 0.534 | 0.723 | 20.2 | |
| MLP Neural NetFormula=SR, Hyperparameter Optimization=default, number of parameters=6012026.03 | -0.015 | 11 | 13.8 | 15.1 |