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Table 1 Final output of the CPI parameters obtained after twenty iterations of linear logistic regression, ANN, linear- and RBF-SVM models

From: Non-invasive detection of fasting blood glucose level via electrochemical measurement of saliva

S. no. Machine learning technique Computational parameters
Accuracy Precision Recall F1 score
1 Linear logistic regression 75.86 ± 2.3 76.76 ± 3.8 75.48 ± 5.4 75.71 ± 2.6
2 ANN 80.7 ± 2.1 81.2 ± 1.7 79.3 ± 3.4 80.2 ± 2.2
3 Linear-SVM 77.93 ± 2.7 77.59 ± 3.5 79.43 ± 4.7 78.11 ± 2.7
4 RBF-SVM 84.09 ± 2.8 83.75 ± 3.3 84.92 ± 4.5 84.06 ± 2.9