Table 4 Classification results of imputed datasets under SVC
From: Missing data imputation, prediction, and feature selection in diagnosis of vaginal prolapse
Imputation Method | Accuracy | F1 | AUC |
|---|---|---|---|
Mean | 0.7113(<e-33) | 0.8177(0.1232e-31) | 0.7595(<e-33) |
EM | 0.6955(<e-33) | 0.8204(<e-33) | 0.7750(0.1232e-31) |
KNN | 0.7715(0.1232e-31) | 0.8445(0.4930e-31) | 0.8201(<e-33) |
DAE | 0.7101(<e-33) | 0.8150(<e-33) | 0.7641(1.1093e-31) |
GAIN | 0.7948(0.4930e-31) | 0.8511(0.1232e-31) | 0.8666(<e-33) |