Table 3
Statistical comparison of the performances of three regression methods on the test set (the Horsehead pillar).
| Method | Hyper-parameters | Max. error(a) | Mean error(a) | RMSE | MSE |
|---|---|---|---|---|---|
| dex | dex | dex | dex | ||
| Linear regression | 0 | 0.37 | 0.026 ± 0.003 | 0.14 | 0.0182 ± 0.0007 |
| Linear regression on asinh(I) | 1 | 0.33 | 0.075 ± 0.002 | 0.11 | 0.0070 ± 0.0003 |
| Random forest | 3 | 0.26 | 0.040 ± 0.002 | 0.09 | 0.0060 ± 0.0002 |
| Method | Hyper-parameters | Max. error(a) | Mean error(a) | RMSE | MSE |
| 10dex | 10dex | 10dex | 10dex | ||
| Linear regression | 0 | 2.34 | 1.062 | 1.38 | 1.043 |
| Linear regression on asinh(I) | 1 | 2.14 | 1.190 | 1.29 | 1.016 |
| Random forest | 3 | 1.82 | 1.096 | 1.23 | 1.014 |
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