From: Missing data imputation, prediction, and feature selection in diagnosis of vaginal prolapse
Imputation methods | FSM(NO.of selected features) | Accuracy | F1 | AUC |
---|---|---|---|---|
Mean | Lasso(20) | 0.7115(0.0075) | 0.8086(0.0058) | 0.6071(0.0068) |
SCAD(41) | 0.7116(0.0078) | 0.8086(0.0059) | 0.6072(0.0075) | |
BAR(7) | 0.6997(0.0073) | 0.8021(0.0056) | 0.5895(0.0067) | |
EM | Lasso(20) | 0.7117(0.0074) | 0.8086(0.0058) | 0.6080(0.0068) |
SCAD(30) | 0.7121(0.0075) | 0.8086(0.0058) | 0.6093(0.0069) | |
BAR(7) | 0.7058(0.0075) | 0.8052(0.0058) | 0.5991(0.0069) | |
KNN | Lasso(20) | 0.7133(0.0073) | 0.8094(0.0056) | 0.6105(0.0073) |
SCAD(38) | 0.7135(0.0073) | 0.8094(0.0057) | 0.6114(0.0070) | |
BAR(7) | 0.7058(0.0075) | 0.8053(0.0058) | 0.5991(0.0069) | |
DAE | Lasso(27) | 0.7022(0.0081) | 0.7977(0.0064) | 0.6113(0.0084) |
SCAD(62) | 0.7080(0.0077) | 0.7987(0.0060) | 0.6271(0.0082) | |
BAR(7) | 0.6932(0.0083) | 0.7943(0.0068) | 0.5926(0.0073) | |
GAIN | Lasso(10) | 0.7921(0.0065) | 0.8495(0.0053) | 0.7536(0.0074) |
SCAD(52) | 0.7952(0.0076) | 0.8517(0.0061) | 0.7573(0.0084) | |
BAR(9) | 0.7943(0.0070) | 0.8508(0.0056) | 0.7574(0.0079) |