Comparison between our RF and MLPQNA against (Stensbo-Smidt et al. 2017) k-NN using the full train set and the best eight features found by Stensbo–Smidt.
| Model . | RMSE . | Median . | η . |
|---|---|---|---|
| RF | 0.264 | −0.020 | 1.86 |
| k-NN | 0.274 | 0.013 | 1.85 |
| MLPQNA | 0.265 | −0.021 | 1.85 |
| Model . | RMSE . | Median . | η . |
|---|---|---|---|
| RF | 0.264 | −0.020 | 1.86 |
| k-NN | 0.274 | 0.013 | 1.85 |
| MLPQNA | 0.265 | −0.021 | 1.85 |
Comparison between our RF and MLPQNA against (Stensbo-Smidt et al. 2017) k-NN using the full train set and the best eight features found by Stensbo–Smidt.
| Model . | RMSE . | Median . | η . |
|---|---|---|---|
| RF | 0.264 | −0.020 | 1.86 |
| k-NN | 0.274 | 0.013 | 1.85 |
| MLPQNA | 0.265 | −0.021 | 1.85 |
| Model . | RMSE . | Median . | η . |
|---|---|---|---|
| RF | 0.264 | −0.020 | 1.86 |
| k-NN | 0.274 | 0.013 | 1.85 |
| MLPQNA | 0.265 | −0.021 | 1.85 |
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