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Table 1 Classification error rates using naïve Bayes (NB), Bayesian networks (BN) and neural networks (NN) in five categorization schemes (K = 2, 3, 4, 5 and 10), based on the final SNP subsets selected

From: Comparison of classification methods for detecting associations between SNPs and chick mortality

   Number of categories (K)
Stratuma Classifier K = 2 K = 3 K = 4 K = 5 K = 10
EL NB 0.124 0.225 0.314 0.329 0.523
  BN 0.207 0.437 0.649 0.674 0.813
  NN 0.270 0.295 0.543 0.662 0.813
EH NB 0.116 0.212 0.330 0.397 0.506
  BN 0.228 0.422 0.653 0.688 0.820
  NN 0.185 0.364 0.560 0.623 0.827
LL NB 0.132 0.221 0.375 0.408 0.523
  BN 0.225 0.403 0.545 0.709 0.824
  NN 0.221 0.401 0.588 0.610 0.831
LH NB 0.151 0.252 0.338 0.405 0.494
  BN 0.261 0.438 0.532 0.681 0.816
  NN 0.278 0.381 0.530 0.534 0.793
  1. a EL = early age-low hygiene; EH = early age-high hygiene; LL = late age-low hygiene; LH = late age-high hygiene.