Table 2 Results of binary combinations of classification models
From: A novel hybrid model to predict concomitant diseases for Hashimoto’s thyroiditis
Model | Precision (p) | Recall (r) | F-measure (F) | Sensitivity | Accuracy |
|---|---|---|---|---|---|
SVM-RF | 0.514 | 0.9 | 0.645 | 0.9 | 0.486 |
SVM-LR | 0.547 | 1.0 | 0.705 | 1.0 | 0.547 |
SVM-KNN | 0.665 | 1.0 | 0.785 | 1.0 | 0.714 |
SVM-MLP | 0.547 | 1.0 | 0.705 | 1.0 | 0.547 |
RF-LR | 0.514 | 0.9 | 0.645 | 0.9 | 0.482 |
RF-KNN | 0.662 | 1.0 | 0.792 | 1.0 | 0.710 |
RF-MLP | 0.514 | 0.9 | 0.645 | 0.9 | 0.480 |
LR-KNN | 0.667 | 1.0 | 0.791 | 1.0 | 0.711 |
LR-MLP | 0.54 | 1.0 | 0.705 | 1.0 | 0.547 |
KNN-MLP | 0.666 | 1.0 | 0.796 | 1.0 | 0.735 |
Hybrid-KNN-MLP | 0.701 | 1.0 | 0.802 | 1.0 | 0.786 |