Table 3. Accuracy of various multiclass models in classifying different ST lineages.
| Model | Selected peaks | ST5 | ST59 | ST239 | Others |
|---|---|---|---|---|---|
| QC | 24 | 0.65 ± 0.05 | 0.85 ± 0.03 | 0.79 ± 0.03 | 0.09 ± 0.07 |
| SNN | 25 | 0.65 ± 0.05 | 0.34 ± 0.05 | 0.25 ± 0.06 | 0.13 ± 0.09 |
| GA_KNN1 | 30 | 0.58 ± 0.05 | 0.63 ± 0.04 | 0.84 ± 0.02 | 0.09 ± 0.07 |
| GA_KNN3 | 26 | 0.73 ± 0.03 | 0.78 ± 0.03 | 0.90 ± 0.02 | 0.13 ± 0.08 |
| GA_KNN5 | 27 | 0.73 ± 0.03 | 0.78 ± 0.03 | 0.94 ± 0.02 | 0.04 ± 0.07 |
| GA_KNN7 | 22 | 0.92 ± 0.03 | 0.81 ± 0.03 | 0.94 ± 0.02 | 0.04 ± 0.07 |
Notes:
QC, QuickClassifier; SNN, supervised neural network; GA, genetic algorithm; KNN, K-Nearest Neighbor.
The number following “GA-KNN” indicated the number of the nearest neighbor used in models; Selected peaks: number of peaks selected by the models. Accuracies were expressed as mean ± standard error.