Table 3 Performance comparison among machine learning algorithms
From: Classification of genomic islands using decision trees and their ensemble algorithms
Method | Sensitivity | Specificity | F-Measure | Accuracy | AUC |
|---|---|---|---|---|---|
CART | 0.813 | 0.807 | 0.811 | 0.810 | 0.855 |
Naive Bayesian | 0.589 | 0.893 | 0.710 | 0.743 | 0.811 |
BayesianNet | 0.604 | 0.914 | 0.727 | 0.760 | 0.839 |
J48 | 0.858 | 0.843 | 0.850 | 0.850 | 0.892 |
Logistic | 0.628 | 0.893 | 0.738 | 0.762 | 0.845 |
Neural Network | 0.659 | 0.849 | 0.742 | 0.754 | 0.833 |
SVM | 0.565 | 0.902 | 0.695 | 0.735 | 0.734 |