Research Article
COVID-19 Propagation Prediction Model Using Improved Grey Wolf Optimization Algorithms in Combination with XGBoost and Bagging-Integrated Learning
Table 2
Correlation analysis of predictor and predicted variables in sample data.
| Predicted variable: cumulative number of confirmed cases in China | Predictor variable | Correlation coefficient | value | Predictor variable | Correlation coefficient | value |
| X1 | 0.034 | >0.05 | X2 | 0.139 | >0.05 | X3 | −0.592 | <0.01 | X4 | 0.538 | <0.01 | X5 | −0.929 | <0.01 | X6 | −0.874 | <0.01 | X7 | 0.536 | <0.01 | X8 | −0.366 | <0.01 | X9 | −0.591 | <0.01 | X10 | 0.485 | <0.01 | X11 | −0.564 | <0.01 | X12 | −0.536 | <0.01 | X13 | −0.762 | <0.01 | X14 | −0.815 | <0.01 | X15 | −0.724 | <0.01 | X16 | −0.574 | <0.01 | X17 | −0.789 | <0.01 | X18 | −0.353 | <0.01 | X19 | −0.651 | <0.01 | X20 | −0.820 | <0.01 | X21 | −0.825 | <0.01 | X22 | −0.969 | <0.01 | X23 | −0.956 | <0.01 | X24 | −0.726 | <0.01 | X25 | −0.727 | <0.01 | X26 | −0.583 | <0.01 | X27 | 0.692 | <0.01 | X28 | −0.216 | <0.01 | X29 | −0.474 | <0.01 | X30 | −0.727 | <0.01 | X31 | −0.882 | <0.01 | X32 | −0.917 | <0.01 | X33 | −0.915 | <0.01 | X34 | 0.715 | <0.01 | X35 | 0.596 | <0.01 | | | |
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