Table 15 Classification methods comparison.
From: An artificial neural network approach for predicting hypertension using NHANES data
Method | Precision | Accuracy | f1-score | AUC |
|---|---|---|---|---|
Our model | 0.578 | 0.732 | 0.474 | 0.77 |
Decision jungle | 0.581 | 0.734 | 0.453 | 0.769 |
Logistic regression | 0.589 | 0.737 | 0.465 | 0.764 |
Support vector machine | 0.59 | 0.737 | 0.464 | 0.759 |
Boosted decision tree | 0.564 | 0.729 | 0.462 | 0.765 |
Bayes point machine | 0.583 | 0.735 | 0.456 | 0.763 |
Synthetic minority oversampling | 0.73 | 0.73 | 0.77 | 0.8 |
