Table 9 Classification results of imputed datasets under elastic Net-LR classifier
From: Missing data imputation, prediction, and feature selection in diagnosis of vaginal prolapse
Imputation Method | Accuracy | F1 | AUC |
|---|---|---|---|
Mean | 0.7111(0.0082) | 0.8094(0.0063) | 0.6032(0.0075) |
EM | 0.7103(0.0082) | 0.8089(0.0064) | 0.6024(0.0074) |
KNN | 0.7122(0.0080) | 0.8098(0.0062) | 0.6058(0.0075) |
DAE | 0.7078(0.0081) | 0.7980(0.0066) | 0.6287(0.0086) |
GAIN | 0.7976(0.0073) | 0.8536(0.0060) | 0.7590(0.0085) |