Table 8 Comparison of classification technique
From: Analysis of diabetes mellitus for early prediction using optimal features selection
No. | Algorithm | Sensitivity % | Specificity % | Positive likelihood ratio | Negative likelihood ratio | Disease prevalence % | Positive predictive value % | Negative predictive value % | Accuracy % |
|---|---|---|---|---|---|---|---|---|---|
1 | SVM | 57.09 | 88.80 | 5.10 | 0.48 | 34.90 | 73.21 | 79.43 | 77.73 |
2 | Random forest | 33.21 | 98.00 | 16.60 | 0.68 | 34.90 | 89.90 | 73.24 | 75.39 |
3 | NB | 61.25 | 80.00 | 3.06 | 0.48 | 34.78 | 62.03 | 79.47 | 73.48 |
4 | Decision tree | 26.49 | 98.20 | 14.72 | 0.75 | 34.90 | 88.75 | 71.37 | 73.18 |
5 | KNN | 46.25 | 72.00 | 1.65 | 0.75 | 34.78 | 46.84 | 71.52 | 63.04 |