Table 5.
Performances of different classifiers tested on DDSM database
| Our method | SVM | GA-SVM | PSO-SVM | Decision tree | |
|---|---|---|---|---|---|
| Sensitivity | 0.9478 | 0.7826 | 0.8261 | 0.8522 | 0.9130 |
| Specificity | 0.9176 | 0.7294 | 0.8353 | 0.8471 | 0.8941 |
| PPV | 0.9397 | 0.7965 | 0.8716 | 0.8829 | 0.9211 |
| NPV | 0.9286 | 0.7126 | 0.7802 | 0.8090 | 0.8837 |
Bold font number indicates the best performance in each line
SVM support vector machine, GA-SVM genetic algorithm support vector machine, PSO-SVM particle swarm optimization support vector machine, PPV positive predictive value, NPV negative predictive value