Research Article
A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
Table 4
The performance of single classifier compared with the integrated classifiers on mammography images.
| | | Accuracy | Sensitivity | Specificity | NPV | PPV | AUC |
| | Naive Bayes-M | 78.87% | 77.42% | 80% | 82.05% | 75.00% | 0.7653 | | SVM-M | 54.93% | 45.16% | 62.5% | 59.52% | 48.28% | 0.5202 | | KNN-M | 67.61% | 58.06% | 75% | 69.77% | 64.29% | 0.6290 | | The integrated classifier (mammography) | 83.10% | 80.05% | 85% | 85% | 80.65% | 0.8089 |
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