TABLE 2.
Error matrix for the classification of the 338 exemplars of four audiometric phenotypes determined by a human expert (rows) and by Quadratic Discriminant Analysis (QDA), Support Vector Machines (SVM), and Random Forests (RF) (columns). Overall accuracy of the three methods was 93.2, 89.9, and 89.3 %, respectively
| Older-normal | Metabolic | Sensory | Metabolic + Sensory | Percent correct | |
|---|---|---|---|---|---|
| QDA | |||||
| Older-normal | 36 | 0 | 1 | 0 | 97.3 |
| Metabolic | 0 | 79 | 0 | 6 | 92.9 |
| Sensory | 0 | 1 | 74 | 3 | 94.9 |
| Metabolic + Sensory | 0 | 9 | 3 | 126 | 91.3 |
| SVM | |||||
| Older-normal | 37 | 0 | 0 | 0 | 100.0 |
| Metabolic | 0 | 70 | 1 | 14 | 82.4 |
| Sensory | 0 | 2 | 76 | 0 | 97.4 |
| Metabolic + Sensory | 0 | 15 | 2 | 121 | 87.7 |
| RF | |||||
| Older-normal | 37 | 0 | 0 | 0 | 100.0 |
| Metabolic | 0 | 71 | 2 | 12 | 83.5 |
| Sensory | 1 | 1 | 73 | 3 | 93.6 |
| Metabolic + Sensory | 0 | 14 | 1 | 123 | 89.1 |