From: Gradient boosting for Parkinson’s disease diagnosis from voice recordings
Metrics | Accuracy Metrics with 95% CI | ||||||
---|---|---|---|---|---|---|---|
LGB | XGB | LR | SVM | RF | KNN | LASSO | |
F1 | 0.839 [0.831–0.847] | 0.810 [0.802–0.819] | 0.771 [0.762–0.780] | 0.730 [0.721–0.739] | 0.810 [0.800–0.819] | 0.744 [0.735–0.753] | 0.763 [0.755–0.7723] |
AUC | 0.898 [0.892–0.905] | 0.891 [0.885–0.898] | 0.839 [0.830–0.847 | 0.838 [0.830–0.846] | 0.884 [0.876–0.892] | 0.841 [0.834–0.848] | 0.870 [0.863–0.877] |
Accuracy | 0.841 [0.833–0.849] | 0.816 [0.809–0.823] | 0.771 [0.762–0.780] | 0.744 [0.735–0.752] | 0.818 [0.810–0.826] | 0.760 [0.752–0.768] | 0.761 [0.753–0.769] |
Sensitivity | 0.839 [0.827–0.850] | 0.801 [0.789–0.813] | 0.777 [0.765–0.790] | 0.704 [0.691–0.716] | 0.795 [0.782–0.808] | 0.712 [0.699–0.725] | 0.782 [0.769–0.794] |
Specificity | 0.844 [0.832–0.855] | 0.830 [0.819–0.841] | 0.764 [0.750–0.778] | 0.784 [0.771–0.798] | 0.841 [0.831–0.852] | 0.807 [0.796–0.818] | 0.741 [0.729–0.754] |
PPV | 0.853 [0.843–0.863] | 0.835 [0.825–0.845] | 0.780 [0.769–0.791] | 0.780 0.769–0.791] | 0.844 [0.834–0.854] | 0.796 [0.786–0.806] | 0.762 [0.753–0.772] |