Table 2. Hyper-parameters, OBB, ROC-AUC, and confusion matrix of donor-specific random forests models.
| Donor (no. of data points) | ntree | mtry | OOB (%) | ROC-AUC | TP | FP | FN | TN |
|---|---|---|---|---|---|---|---|---|
| A (170) | 100 | 4 | 24.41 | 0.740 | 39 | 18 | 13 | 57 |
| B (155) | 150 | 2 | 38.79 | 0.650 | 28 | 27 | 18 | 43 |
| C (232) | 250 | 3 | 32.18 | 0.813 | 67 | 29 | 27 | 51 |
| D (199) | 400 | 4 | 10.07 | 0.968 | 76 | 5 | 10 | 58 |
| E (179) | 250 | 1 | 19.40 | 0.854 | 58 | 9 | 17 | 50 |
| F (212) | 250 | 1 | 26.42 | 0.801 | 101 | 2 | 40 | 16 |
ntree, number of trees; mtry, number of variables selected for the best split at each node; OBB, out-of-bag error; ROC-AUC, area under receiver operating characteristics curve; TP, true positive; FP, false positive; FN, false negative; TN, true negative.