| Sensitivity | Specificity | Accuracy | ||
---|---|---|---|---|---|
Better-hearing ear | Training set (Community A) | Decision Tree (DT) | 95.35% | 86.85% | 91.20% |
Support Vector Machine (SVM) | 100.00% | 100.00% | 100.00% | ||
Random Forest (RF) | 91.32% | 94.97% | 93.10% | ||
Multilayer Perceptron (MLP) | 78.29% | 56.98% | 67.88% | ||
Test set (Community B) | Decision Tree (DT) | 93.50% | 90.56% | 91.92% | |
Support Vector Machine (SVM) | 100.00% | 33.57% | 64.29% | ||
Random Forest (RF) | 94.31% | 92.31% | 93.23% | ||
Multilayer Perceptron (MLP) | 90.65% | 51.05% | 69.36% | ||
Worse-hearing ear | Training set (Community A) | Decision Tree (DT) | 97.53% | 71.54% | 89.93% |
Support Vector Machine (SVM) | 100.00% | 100.00% | 100.00% | ||
Random Forest (RF) | 98.21% | 77.51% | 92.15% | ||
Multilayer Perceptron (MLP) | 99.89% | 11.38% | 73.99% | ||
Test set (Community B) | Decision Tree (DT) | 97.58% | 80.69% | 91.17% | |
Support Vector Machine (SVM) | 100.00% | 34.16% | 75.00% | ||
Random Forest (RF) | 99.39% | 84.65% | 93.80% | ||
Multilayer Perceptron (MLP) | 100.00% | 19.31% | 69.36% |