Table 5.
Performance achieved by scikit ML on the fingerprints descriptors.
| Methods (Parameters) | Main Dataset | Validation Dataset | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Sen | Spc | Acc | MCC | AUC | Sen | Spc | Acc | MCC | AUC | |
| RF (n_estimators = 800) | 77.51 | 77.16 | 78.33 | 0.56 | 0.86 | 80.85 | 75.73 | 78.29 | 0.57 | 0.85 |
| KNN (n_neighbors = 8,algorithm = ‘ball_tree',weights = ‘distance') | 75.98 | 70.69 | 73.32 | 0.47 | 0.81 | 77.78 | 70.94 | 74.36 | 0.49 | 0.79 |
| Ridge (alpha = 1) | 75.76 | 71.55 | 73.64 | 0.47 | 0.81 | 76.92 | 70.09 | 73.5 | 0.47 | 0.80 |
| Extratree (n_estimator = 300) | 78.6 | 73.71 | 76.14 | 0.52 | 0.84 | 78.46 | 75.56 | 77.01 | 0.54 | 0.82 |