Table 2 - Performance of each classifier using the features selected by the wrapper method. SVM = Support Vector Machine; MLP = Multilayer Perceptron; Instance-Based Algorithm (IBA) derived from k-nearest neighbors (IBk) (k = 1, k = 3, k = 5); AUC = Area under the ROC curve
Classifier | AUC | Sensitivity | Specificity | Accuracy (%) | Number of Features |
|---|---|---|---|---|---|
SVM | 0.842 | 0.800 | 0.885 | 87.8 | 15 |
IBk with k = 1 | 0.798 | 0.800 | 0.769 | 78.2 | 13 |
IBk with k = 3 | 0.867 | 0.750 | 0.885 | 82.6 | 14 |
IBk with k = 5 | 0.969 | 0.750 | 0.962 | 86.9 | 9 |
MLP | 0.965 | 1.000 | 0.923 | 95.6 | 6 |