Table 8.
Performance of the machine learning classifiers for private MOX2-5 datasets.
| ML classifier models | Mean accuracy | Precision | Recall | F1 | MCC |
|---|---|---|---|---|---|
| SVC (kernel = 'linear') | 96.03 | 96.00 | 96.00 | 96.00 | 95.10 |
| SVC (kernel = 'rbf') | 47.01 | 43.00 | 47.00 | 45.00 | 30.69 |
| GaussianNB () | 93.40 | 93.00 | 93.00 | 93.00 | 91.80 |
| DecisionTreeClassifier (criterion = "gini") | 96.10 | 96.00 | 96.00 | 96.00 | 96.10 |
| DecisionTreeClassifier (criterion = "entropy") | 96.10 | 96.00 | 96.00 | 96.00 | 96.10 |
| RandomForestClassifier (n_estimators = 50) | 95.80 | 95.00 | 96.00 | 95.00 | 94.88 |
| RandomForestClassifier (n_estimators = 100) | 95.80 | 95.00 | 96.00 | 95.00 | 94.88 |
| KNeighborsClassifier (n_neighbors = 2) | 70.98 | 70.00 | 71.00 | 70.00 | 66.31 |
| KNeighborsClassifier (n_neighbors = 4) | 66.54 | 66.00 | 67.00 | 66.00 | 61.30 |
| DummyClassifier | 35.18 | 35.00 | 35.00 | 35.00 | 00.00 |