Table 4.
Performance of different machine learning methods in 202 countries
| Methods | ACC | M_P | M_R | M_F1 | K_Score |
|---|---|---|---|---|---|
| Linear Regression Classification |
0.6127 |
0.5138 |
0.5472 |
0.5048 |
0.3786 |
| Support Vector Machine |
0.5943 |
0.4963 |
0.5080 |
0.4998 |
0.3210 |
| k-Nearest Neighbor |
0.6799 |
0.5962 |
0.5516 |
0.5592 |
0.4156 |
| Decision Tree Classification |
0.6681 |
0.6027 |
0.6152 |
0.6064 |
0.4605 |
| Random Forest Classification | 0.7527 | 0.6724 | 0.6754 | 0.6698 | 0.5841 |
ACC – accuracy, M_P – macro precision, M_R – macro recall, M_F1 – macro F1-score, K_Score – kappa-coefficient