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| Predictor set | Model | ||
|---|---|---|---|
| CPH | RF | GBC | |
| QA | 0.736 | 0.736 | 0.796 |
| QA+ | 0.743 | 0.799 | 0.810 |
| T | 0.788 | 0.810 | 0.826 |
Predictor set T and GBC modelling constantly perform better than their counterparts. The results conform to the pattern observed in internal cross-validation.
CPH, Cox proportional hazards; GBC, gradient boosting classifier; RF, random forest.
