Table 1.
The values of the evaluation indices obtained for all developed algorithms concerning all segments.
| Model | R 2 | MSE | AARE% | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Training | Test | Total | Training | Test | Total | Training | Test | Total | |
| Decision tree | 1 | 0.9877749 | 0.998612 | 0 | 874.94053 | 89.61655 | 0 | 1.962774 | 0.201039 |
| AdaBoost | 0.999816 | 0.9873096 | 0.998396 | 11.68284 | 908.2457 | 103.5141 | 0.049028 | 2.0167033 | 0.250568 |
| Random forest | 0.998877 | 0.9938321 | 0.998306 | 71.45457 | 441.43629 | 109.3503 | 0.522292 | 1.2746318 | 0.599351 |
| KNN | 0.995793 | 0.9909112 | 0.995245 | 267.7302 | 650.47875 | 306.9336 | 0.758256 | 1.5837447 | 0.842808 |
| Ensemble learning | 0.999478 | 0.9941084 | 0.998869 | 33.19793 | 421.6589 | 72.98639 | 0.311831 | 1.2146281 | 0.404301 |
| CNN | 0.999489 | 0.9995753 | 0.999499 | 32.53207 | 30.393282 | 32.31301 | 0.339601 | 0.3274238 | 0.338354 |
| SVR | 0.995183 | 0.9980559 | 0.995517 | 306.5239 | 139.13604 | 289.3791 | 0.802766 | 0.6995348 | 0.792193 |
| MLP-ANN | 0.98711 | 0.9895765 | 0.987411 | 820.2769 | 746.00069 | 812.6691 | 1.660529 | 1.648544 | 1.659302 |
| Linear regression | 0.984623 | 0.9853604 | 0.984731 | 978.5468 | 1047.7514 | 985.6351 | 1.821798 | 1.9798891 | 1.837991 |
| Ridge regression | 0.984623 | 0.9853636 | 0.984732 | 978.5656 | 1047.5161 | 985.6279 | 1.821681 | 1.9782273 | 1.837716 |