Table 2:
Model | Training Sample | Testing Sample | ||||||
---|---|---|---|---|---|---|---|---|
LR | DT | ANN | SVM | LR | DT | ANN | SVM | |
Sensitivity | 0.72 | 0.88 | 0.74 | 0.85 | 0.73 | 0.85 | 0.75 | 0.53 |
Specificity | 0.63 | 0.46 | 0.60 | 0.67 | 0.65 | 0.46 | 0.60 | 0.68 |
Positive predictive value | 0.15 | 0.13 | 0.14 | 0.19 | 0.16 | 0.13 | 0.15 | 0.14 |
Negative predictive value | 0.96 | 0.97 | 0.96 | 0.98 | 0.96 | 0.97 | 0.96 | 0.94 |
Accuracy | 0.64 | 0.50 | 0.62 | 0.68 | 0.65 | 0.49 | 0.62 | 0.67 |
LR: logistic regression, DT: decision tree, ANN: artificial neural network, SVM: support vector machine