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Table 4 Results on TMA dataset for the two proteins.

From: A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays

  Acc Spec Sens AUC Brier
HierNB Model 0.65 [0.62–0.68] 0.71 [0.66–0.74] 0.60 [0.56–0.62] 0.69 [0.689–0.693] 0.41 [0.39–0.42]
StNB Model 0.58 [0.54–0.61] 0.58 [0.54–0.62] 0.57 [0.53–0.61] 0.62 [0.617–0.622] 0.47 [0.46–0.48]
  1. Acc = Accuracy, Spec = specificity, Sens = Sensitivity, Brier = Brier Score. In brackets the 95% confidence intervals for the estimates, AUC = area under the ROC.