Table 4.
Prediction error for a method containing an evolutionary approach.
| Test dataset | Dataset | |||
|---|---|---|---|---|
| No. | Period | Training | Test | |
| 1 | 2016–01-28 | 2016–02-27 | 0.02054 | 0.01467 |
| 2 | 2016–04-22 | 2016–05-22 | 0.02000 | 0.02425 |
| 3 | 2016–09-15 | 2016–10-15 | 0.02055 | 0.01314 |
| 4 | 2016–11-05 | 2016–12-05 | 0.02051 | 0.01913 |
| 5 | 2017–10-31 | 2017–11-30 | 0.02008 | 0.01782 |
| 6 | 2018–06-01 | 2018–07-01 | 0.01889 | 0.01917 |
| 7 | 2018–07-21 | 2018–08-20 | 0.01806 | 0.03306 |
| 8 | 2019–01-16 | 2019–02-15 | 0.01981 | 0.01640 |
| 9 | 2019–06-01 | 2019–07-01 | 0.02019 | 0.02948 |
| 10 | 2019–10-27 | 2019–11-26 | 0.02093 | 0.02476 |
| MAPE (–) | 0.01996 | 0.02119 | ||
The best and the worst results on the test datasets are emphasised in bold.