Table 5.
SVM classification results. The best results are achieved using the linear kernel and including both spectral slopes and fold change asymmetry statistics in the classification.
| Mean Accuracy Rate | Mean Sensitivity | Mean Specificity | |
|---|---|---|---|
|
| |||
| Slopes Only | |||
|
| |||
| Linear | 0.6268 | 0.7039 | 0.4952 |
| Quadratic | 0.6027 | 0.6855 | 0.4607 |
| Radial Basis | 0.6017 | 0.5978 | 0.6099 |
|
| |||
| Slopes + Asymmetry t | |||
|
| |||
| Linear | 0.6731 | 0.6685 | 0.6819 |
| Quadratic | 0.6684 | 0.6930 | 0.6314 |
| Radial Basis | 0.6332 | 0.6901 | 0.5474 |
|
| |||
| Slopes + Asymmetry f | |||
|
| |||
| Linear | 0.7659 | 0.7250 | 0.8379 |
|
| |||
| Quadratic | 0.7195 | 0.7414 | 0.6856 |
| Radial Basis | 0.7296 | 0.7800 | 0.6513 |