83.33% ± 18.3 | Class Prediction |
---|
| control | infected | normal |
control |
20
| 0 | 3 |
infected | 0 |
14
| 0 |
normal | 0 | 0 |
3
|
no class | 0 | 0 | 0 |
error | 0 | 0 | 3 |
- The classifier created was applied to the training set to assign gel maps with respect to disease state. The classification matrix shows an overview of the classification of the gel maps. Gels that were correctly classified are displayed in bold type. A classifier containing 16 biomarkers was used to discriminate between the 3 groups with 83.33% ± 18.3 accuracy. A single protein was able to discriminate between control and infected samples with 100% accuracy.