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Table 1 Classification performance on the test sets.

From: Phenotype forecasting with SNPs data through gene-based Bayesian networks

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   
  1. 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.