| Var Num |
Methods |
Performance of Training dataset |
Performance of Independent Test dataset |
| CC |
RMSE |
MAE |
RAE |
RRSE |
CC |
RMSE |
MAE |
RAE |
RRSE |
| 5 |
Liner regression |
0.4549 |
0.8905 |
0.6341 |
0.8749 |
0.8906 |
0.4577 |
0.7680 |
0.5664 |
0.9163 |
0.9021 |
| Gauss Process |
0.4472 |
0.9451 |
0.6779 |
0.9353 |
0.9452 |
0.4438 |
0.8036 |
0.6173 |
0.9987 |
0.9940 |
| REP Tree |
0.4545 |
0.8933 |
0.6346 |
0.8756 |
0.8934 |
0.4103 |
0.8051 |
0.5904 |
0.9551 |
0.9457 |
| Random Forest |
0.4820 |
0.8764 |
0.6236 |
0.8605 |
0.8765 |
0.4342 |
0.7833 |
0.5750 |
0.9302 |
0.9201 |
| 15 |
Liner regression |
0.4643 |
0.8857 |
0.6288 |
0.8676 |
0.8858 |
0.4645 |
0.7672 |
0.5665 |
0.9164 |
0.9012 |
| Gauss Process |
0.4361 |
0.9010 |
0.6400 |
0.8831 |
0.9011 |
0.4435 |
0.7930 |
0.5882 |
0.9515 |
0.9315 |
| REP Tree |
0.4699 |
0.8844 |
0.6248 |
0.8620 |
0.8845 |
0.4221 |
0.7978 |
0.5877 |
0.9508 |
0.9371 |
| Random Forest |
0.5858 |
0.8318 |
0.5840 |
0.8058 |
0.8318 |
0.4385 |
0.7725 |
0.5697 |
0.9216 |
0.9075 |
| 30 |
Liner regression |
0.4697 |
0.8829 |
0.6257 |
0.8634 |
0.8829 |
0.4698 |
0.7655 |
0.5641 |
0.9125 |
0.8992 |
| Gauss Process |
0.4335 |
0.9021 |
0.6396 |
0.8825 |
0.9022 |
0.4390 |
0.7995 |
0.5909 |
0.9559 |
0.9392 |
| REP Tree |
0.4676 |
0.8892 |
0.6241 |
0.8611 |
0.8863 |
0.4209 |
0.7987 |
0.5877 |
0.9507 |
0.9382 |
| Random Forest |
0.6015 |
0.8283 |
0.5815 |
0.8023 |
0.8284 |
0.4150 |
0.7816 |
0.5767 |
0.9330 |
0.9182 |
| 50 |
Liner regression |
0.4697 |
0.8829 |
0.6258 |
0.8634 |
0.8829 |
0.4698 |
0.7655 |
0.5641 |
0.9125 |
0.8992 |
| Gauss Process |
0.4271 |
0.9139 |
0.6497 |
0.8964 |
0.9141 |
0.4306 |
0.8426 |
0.6195 |
1.0022 |
0.9898 |
| REP Tree |
0.4736 |
0.8822 |
0.6214 |
0.8574 |
0.8823 |
0.4124 |
0.8086 |
0.5926 |
0.9586 |
0.9498 |
| Random Forest |
0.5964 |
0.8285 |
0.5813 |
0.8021 |
0.8286 |
0.3917 |
0.7901 |
0.5833 |
0.9436 |
0.9281 |
| 100 |
Liner regression |
0.4697 |
0.8828 |
0.6257 |
0.8634 |
0.8829 |
0.4698 |
0.7655 |
0.5641 |
0.9126 |
0.8992 |
| Gauss Process |
0.4219 |
0.9197 |
0.6519 |
0.8995 |
0.9198 |
0.4240 |
0.8543 |
0.6269 |
1.0142 |
1.0035 |
| REP Tree |
0.4784 |
0.8793 |
0.6194 |
0.8546 |
0.8794 |
0.4091 |
0.8130 |
0.5957 |
0.9637 |
0.9550 |
| Random Forest |
0.5948 |
0.8289 |
0.5804 |
0.8008 |
0.8290 |
0.3646 |
0.7998 |
0.5911 |
0.9562 |
0.9395 |
| 300 |
Liner regression |
0.4696 |
0.8829 |
0.6258 |
0.8634 |
0.8830 |
0.4698 |
0.7655 |
0.5641 |
0.9125 |
0.8992 |
| Gauss Process |
0.4116 |
0.9149 |
0.6490 |
0.8956 |
0.9150 |
0.4109 |
0.8241 |
0.6110 |
0.9884 |
0.9681 |
| REP Tree |
0.4787 |
0.8796 |
0.6186 |
0.8535 |
0.8798 |
0.4703 |
0.8144 |
0.5912 |
0.9564 |
0.9567 |
| Random Forest |
0.5996 |
0.8256 |
0.5783 |
0.7979 |
0.8256 |
0.3639 |
0.8003 |
0.5912 |
0.5964 |
0.9401 |
| all |
Liner regression |
0.4703 |
0.8838 |
0.6263 |
0.8620 |
0.8829 |
0.4630 |
0.7697 |
0.5668 |
0.9221 |
0.9083 |
| Gauss Process |
0.3885 |
0.9317 |
0.6570 |
0.9066 |
0.9318 |
0.3988 |
0.8359 |
0.6183 |
1.0002 |
0.9819 |
| REP Tree |
0.4739 |
0.8825 |
0.6202 |
0.8557 |
0.8826 |
0.4233 |
0.7967 |
0.5880 |
0.9513 |
0.9538 |
| Random Forest |
0.4880 |
0.8732 |
0.6212 |
0.8572 |
0.8732 |
0.4469 |
0.7787 |
0.5717 |
0.9249 |
0.9148 |
|
