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Table 4 Performance of utilizing variable numbers of genetic features in different classifiers to predict diabetic nephropathy.

From: An interpretable rule-based diagnostic classification of diabetic nephropathy among type 2 diabetes patients

Classifier No. of features Accuracy (%) Sensitivity (%) Specificity (%)
Decision tree 4 60.43 54.70 66.37
Random forest 12 53.91 59.83 47.79
SVM 13 53.04 67.65 31.9
Naïve Bayes 13 56.09 58.12 53.98