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. 2018 Dec 5;13(12):e0207840. doi: 10.1371/journal.pone.0207840

Table 3. Performance of SVM models on NIPT prediction using different parameter setting.

Chr21 Group "N" & "P" Group "Unclassified"
Model e Real status Support vector number Prediction Sens. f Spec. Prediction Sens. Spec.
N P N P
SVM-RBF-opt N 365 4672 0 100.00% 100.00% 57 0 100.00% 100.00%
P 19 0 19 0 4
SVM-linear-opt N 2 4672 0 100.00% 100.00% 57 0 0.00% 100.00%
P 2 0 19 4 0
SVM-RBF-opt-w N 478 4672 0 100.00% 100.00% 57 0 100.00% 100.00%
P 19 0 19 0 4
SVM-linear-opt-w N 2 4672 0 100.00% 100.00% 57 0 0.00% 100.00%
P 2 0 19 4 0
Chr18 Group "N" & "P" Group "Unclassified"
Model Real status Support vector number Prediction Sens. Spec. Prediction Sens. Spec.
N P N P
SVM-RBF-opt N 106 4697 0 100.00% 100.00% 44 0 100.00% 100.00%
P 7 0 7 0 4
SVM-linear-opt N 2 4697 0 85.71% 100.00% 44 0 0.00% 100.00%
P 2 1 6 4 0
SVM-RBF-opt-w N 303 4697 0 100.00% 100.00% 44 0 100.00% 100.00%
P 6 0 7 0 4
SVM-linear-opt-w N 3 4697 0 85.71.00% 100.00% 44 0 0.00% 100.00%
P 1 1 6 4 0
Chr13 Group "N" & "P" Group "Unclassified"
Model Real status Support vector number Prediction Sens. Spec. Prediction Sens. Spec.
N P N P
SVM-RBF-opt N 1976 4706 0 100.00% 100.00% 42 0 NA 100.00%
P 4 0 4 0 0
SVM-linear-opt N 2 4706 0 100.00% 100.00% 42 0 NA 100.00%
P 2 0 4 0 0
SVM-RBF-opt-w N 2070 4706 0 100.00% 100.00% 42 0 NA 100.00%
P 4 0 4 0 0
SVM-linear-opt-w N 2 4706 0 100.00% 100.00% 42 0 NA 100.00%
P 2 0 4 0 0

Four types of SVM models were compared in both internal and external validation for each of chromosome 13/18/21.

e w means employing class weight to adjust parameter C; opt means employing optimization for parameters C and gamma in cross validation.

f Sens. is short for sensitivity; Spec. is short for specificity.