Table 1.
Model | SNP based | Meta-variable based | Haplotype based | Majority Classifier | |||
Classification Accuracies (%) and K statistics | CA | K-stat | CA | K-stat | CA | K-stat | CA |
Sampling test 1 | 55.71 | 0.09 | 64.28 | 0.26 | 57.14 | 0.12 | 51.43 |
Sampling test 2 | 55 | 0.07 | 59.28 | 0.16 | 53.57 | 0.04 | 51.43 |
Sampling test 3 | 63.57 | 0.25 | 67.86 | 0.34 | 55 | 0.07 | 51.43 |
Sampling test 4 | 62.14 | 0.22 | 65.72 | 0.29 | 49.29 | -0.04 | 51.43 |
Sampling test 5 | 58.57 | 0.15 | 64.28 | 0.26 | 57.85 | 0.13 | 51.43 |
Mean values on test sets | 58.99 | 0.16 | 64.28 | 0.26 | 54.57 | 0.06 | 51.43 |
95% Confidence Interval | 54.28–63.72 | 60.36–68.2 | 50.34–58.80 | ||||
Standard Deviation | 3.8 | 3.16 | 3.4 | ||||
Standard Error | 1.7 | 1.41 | 1.52 |
The table summarizes the results obtained by repeating 5 times a random sampling hold-out scheme in which 75% of the dataset (216 affected and 203 unaffected individuals) was employed as training set and the remaining 25% as test set (72 affected and 68 unaffected individuals). In particular, the table shows the classification accuracies obtained on the test sets by the single-SNP BN, the meta-variable BN and the haplotype BN, the accuracies of the majority classifier and the k-statistics.