Table 16 Classification results of datasets after feature selection under Elastic Net-LR classifier
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) | 0.7143(0.0075) | 0.8107(0.0063) | 0.6092(0.0064) |
SCAD(41) | 0.7115(0.0112) | 0.8090(0.8091) | 0.6056(0.0098) | |
BAR(7) | 0.7019(0.0100) | 0.8036(0.0077) | 0.5916(0.0080) | |
EM | Lasso(20) | 0.7148(0.0079) | 0.8109(0.0064) | 0.6106(0.0063) |
SCAD(30) | 0.7135(0.0092) | 0.8098(0.0072) | 0.6097(0.0080) | |
BAR(7) | 0.7068(0.0082) | 0.8061(0.0063) | 0.5996(0.0070) | |
KNN | Lasso(20) | 0.7139(0.0078) | 0.8099(0.0060) | 0.6108(0.0073) |
SCAD(38) | 0.7142(0.0076) | 0.8101(0.0059) | 0.6115(0.0070) | |
BAR(7) | 0.7068(0.0082) | 0.8061(0.0063) | 0.5996(0.0070) | |
DAE | Lasso(27) | 0.7024(0.0089) | 0.7978(0.0066) | 0.6115(0.0099) |
SCAD(62) | 0.6939(0.0064) | 0.7953(0.0054) | 0.5921(0.0061) | |
BAR(7) | 0.6939(0.0064) | 0.7953(0.0054) | 0.5921(0.0061) | |
GAIN | Lasso(10) | 0.7923(0.0063) | 0.8497(0.0052) | 0.7538(0.0071) |
SCAD(52) | 0.7952(0.0069) | 0.8516(0.0058) | 0.7580(0.0072) | |
BAR(9) | 0.7944(0.0070) | 0.8508(0.0056) | 0.7575(0.0079) |