Table 2.
Evaluating transductive performance with supervised GRN inferring methods on balanced datasets.
| Methods |
E. coli |
S. cerevisiae |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Accuracy | Precision | Recall | MCC | AUC | Accuracy | Precision | Recall | MCC | AUC | |
| SVM | 0.688 ± 0.000 | 0.762 ± 0.000 | 0.547 ± 0.000 | 0.393 ± 0.000 | 0.757 ± 0.000 | 0.575 ± 0.000 | 0.586 ± 0.000 | 0.506 ± 0.000 | 0.151 ± 0.000 | 0.601 ± 0.000 |
| RF | 0.770 ± 0.000 | 0.800 ± 0.000 | 0.721 ± 0.000 | 0.544 ± 0.000 | 0.837 ± 0.000 | 0.708 ± 0.000 | 0.730 ± 0.000 | 0.658 ± 0.000 | 0.418 ± 0.000 | 0.773 ± 0.000 |
| GRGNN | 0.786 ± 0.034 | 0.779 ± 0.047 | 0.875 ± 0.031 | 0.605 ± 0.047 | 0.903 ± 0.009 | 0.782 ± 0.044 | 0.786 ± 0.053 | 0.827 ± 0.043 | 0.571 ± 0.083 | 0.880 ± 0.010 |