Table 1.
Performance metrics of generalized linear models (GLMs) and random forests of bat roost occupancy and abundance.
| Response Variable | Set | Model | Response Error | RMSE | MAE | R 2 | AUC |
|---|---|---|---|---|---|---|---|
| Occupancy (presence/absence of bats) |
Training (n = 380) |
GLM | 0.48 | 0.45 | 0.42 | 0.12 | 0.7 |
| Random forest | 0.48 | 0.41 | 0.04 | 0.61 | |||
| Test (n = 94) |
GLM | 0.46 | 0.46 | 0.43 | 0.02 | 0.59 | |
| Random forest | 0.51 | 0.43 | 0 | 0.49 | |||
| Abundance (roost size) |
Training (n = 255) |
GLM | 670 | 631 | 314 | 0.14 | |
| Random forest | 643 | 312 | 0.09 | ||||
| Test (n = 60) |
GLM | 744 | 711 | 320 | 0.1 | ||
| Random forest | 709 | 327 | 0.08 |
RMSE—root-mean-square error, MAE—mean absolute error, AUC—area under the receiver operating characteristic curve.