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Table 11 Comparison of the performance of Bayesian Network classifier (BN) using different search algorithms: K2, Hill Climbing, Repeated Hill Climber, LAGD Hill Climbing, TAN, Tabu and Simulated Annealing without using Sampling

From: Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project

  K2 Hill Climbing Repeated Hill Climber LAGD Hill Climbing TAN Tabu Simulated Annealing
Sensitivity 37.70% 37.70% 37.70% 48.11% 57.09% 37.94% 53.65%
Specificity 93.21% 93.21% 93.21% 91.44% 90.71% 93.19% 90.97%
Precision 51.20% 51.20% 51.20% 32.63% 24.57% 50.89% 27.44%
F-score 43.42% 43.42% 43.42% 38.89% 34.35% 43.47% 36.31%
RMSE 0.34 0.34 0.34 0.34 0.34 0.3 0.3
AUC 0.82 0.82 0.82 0.81 0.83 0.81 0.82