TABLE 5.
Naive Bayes classification results from the VF training cohort on the 10,000-peptide microarray using the 96 predictor peptidesa
| Data set used, training (hold-out expt) | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) | Accuracy (%) |
|---|---|---|---|---|---|
| VF, normal | 100 | 97 | 97 | 100 | 98 |
| VF, influenza vaccine | 100 | 91 | 99 | 100 | 99 |
| VF, normal, influenza vaccine | 100 | 96 | 96 | 100 | 98 |
| 0 (CF titer, influenza vaccine | 100 | 82 | 76 | 100 | 88 |
| LOOCV, no-hold-out (all data) | 100 | 92 | 92 | 100 | 96 |
| For comparison | |||||
| CF titer (IDCF results) | 87 | 100 | 100 | 50 | 88 |
a
Hold-out splits all data randomly into 70% train/30% predict. The results are from 20 iterations of random hold-outs.