Type of imputation on the dataset (N = 444) | Performance function | One-rule | Decision tree | Logistic regression | Random forest | AdaBoost | Support vector machine |
---|---|---|---|---|---|---|---|
Complete cases | AUC | 0.74+/−0.05 | 0.90+/−0.03 | 0.93+/−0.04 | 0.94+/−0.01 | 0.92+/−0.02 | 0.92+/−0.03 |
Sensitivity | 0.87+/−0.10 | 0.88+/−0.07 | 0.92+/−0.03 | 0.90+/−0.03 | 0.91+/−0.02 | 0.94+/−0.03 | |
Specificity | 0.60+/−0.18 | 0.74+/−0.15 | 0.70+/−0.08 | 0.78+/−0.07 | 0.71+/−0.06 | 0.67+/−0.07 | |
Categorical variable encoding the missingness | AUC | 0.73+/−0.04 | 0.88+/−0.02 | 0.91+/−0.01 | 0.92+/−0.02 | 0.90+/−0.01 | 0.89+/−0.03 |
Sensitivity | 0.92+/−0.07 | 0.88+/−0.07 | 0.92+/−0.03 | 0.91+/−0.02 | 0.91+/−0.03 | 0.93+/−0.03 | |
Specificity | 0.42+/−0.05 | 0.61+/−0.18 | 0.60+/−0.07 | 0.68+/−0.06 | 0.60+/−0.06 | 0.51+/−0.07 | |
Mean/mode | AUC | 0.69+/−0.05 | 0.85+/−0.02 | 0.88+/−0.02 | 0.87+/−0.02 | 0.87+/−0.02 | 0.86+/−0.04 |
Sensitivity | 0.94+/−0.05 | 0.92+/−0.04 | 0.94+/−0.02 | 0.93+/−0.02 | 0.93+/−0.02 | 0.96+/−0.02 | |
Specificity | 0.31+/−0.12 | 0.56+/−0.10 | 0.54+/−0.05 | 0.56+/−0.05 | 0.53+/−0.05 | 0.47+/−0.06 | |
Random forest | AUC | 0.79+/−0.02 | 0.95+/−0.02 | 0.96+/−0.01 | 0.96+/−0.01 | 0.96+/−0.01 | 0.94+/−0.03 |
Sensitivity | 0.97+/−0.04 | 0.94+/−0.04 | 0.96+/−0.02 | 0.94+/−0.02 | 0.95+/−0.01 | 0.96+/−0.01 | |
Specificity | 0.60+/−0.06 | 0.78+/−0.09 | 0.75+/−0.05 | 0.81+/−0.04 | 0.76+/−0.04 | 0.75+/−0.05 |