Toward a hemorrhagic trauma severity score: fusing five physiological biomarkers

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]

Class	Frequency (%)
Class	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%)

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

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