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Table 3 Application of two different algorithms (linear support vector machine and ensemble bagged decision tree) to the five(5) unique SFRP data sets; [100][D1], [100][D2], [100][D3], [100][D4] and [100][D5]

From: Toward a hemorrhagic trauma severity score: fusing five physiological biomarkers

Class Frequency (%)
D1 D2 D3 D4 D5
0 56 43 37 43 53
1 14 20 27 18 17
2 5 18 7 15 13
3 19 17 11 24 17
4 6 2 18 0 0
SVM-L accuracy (%) 78.3 ± 0.5 92.7 ± 0.5 78.3 ± 2.4 88.3 ± 0.5 86.7 ± 0.9
EBDT accuracy (%) 83.3 ± 1.2 96.3 ± 0.9 72.3 ± 0.9 90.0 ± 0.0 87.7 ± 1.2
Class with the highest confusion (TPR—sensitivity for EBDT) 4 (17%) 4 (0%) 2 (14%) 2 (60%) 2 (77%)
  1. The table presents the fraction of the total observations for each class for each dataset and corresponding cross-validated accuracies for both classifiers. The confusion (true positive rates (TPR)) was correlated to the percentage of observations of the class