Table 13 Comparison of the RMSE (normalised) and training times for best found ELM and MLP solutions for given regression datasets
From: Extreme learning machine versus classical feedforward network
Dataset | Model | RMSE | Training time\(^{1}\) |
|---|---|---|---|
Auto MPG | ELM (own) | 0.0751 | 1.5 min |
MLP (own) | 0.0692 | 1.5 h | |
Bank | ELM (own) | 0.0000 | 19 min |
MLP (own) | 0.0692 | 7.5 h | |
California housing | ELM (own) | 0.1627 | 1 h |
MLP (own) | 0.1307 | 20 h | |
Delta ailerons | ELM (own) | 0.0000 | 15 min |
MLP (own) | 0.0437 | 7 h | |
Machine CPU | ELM (own) | 0.1116 | 1.5 min |
MLP (own) | 0.1015 | 1 h | |
Servo | ELM (own) | 0.1433 | 1.5 min |
MLP (own) | 0.0373 | 30 min |