Table 3 Model performance evaluation with test data set, “A case study performed in 2019-20 to develop a Machine Learning-algorithm to estimate the incidence of Diabetes Mellitus in France”
LDA | LR | FDA | C5 | |
|---|---|---|---|---|
Accuracy | 0,67 | 0,65 | 0,66 | 0,64 |
95% CI: | (0,66-0,68) | (0,64-0,66) | (0,65-0,67) | (0,63-0,65) |
No Information Rate: | 0,998 | 0,998 | 0,998 | 0,998 |
P-Value [Acc > NIR]: | 1000 | 1000 | 1000 | 1000 |
Kappa | 0,003 | 0,004 | 0,002 | 0,003 |
McNemar’s Test P-Value | <2e-16 | <2e-16 | <2e-16 | <2e-16 |
Sensitivity | 0,625 | 0,750 | 0,563 | 0,625 |
Specificity | 0,673 | 0,650 | 0,661 | 0,640 |
Pos Pred Value | 0,003 | 0,004 | 0,003 | 0,003 |
Neg Pred Value | 0,999 | 0,999 | 0,999 | 0,999 |
F1-statistics | 2,50 | 3,0 | 2252 | 2,50 |
Detection Rate | 0,001 | 0,001 | 0,001 | 0,001 |
Balanced Accuracy | 0,649 | 0,700 | 0,612 | 0,633 |