Table 3 The performance of machine learning algorithms
From: Prediction of violence in male schizophrenia using sMRI, based on machine learning algorithms
Algorithms | AUC | balanced Accuracy | Kappa | Sensitivity | Specificity |
|---|---|---|---|---|---|
svm | 0.8410(0.6826–0.9995) | 0.8231 | 0.6429 | 0.8000 | 0.8462 |
glmnet | 0.7692(0.5841–0.9544) | 0.7462 | 0.4948 | 0.8000 | 0.6923 |
rpart | 0.7179(0.5463–0.8896) | 0.7179 | 0.4315 | 0.6667 | 0.7692 |
rf | 0.8077(0.6384–0.9770) | 0.7410 | 0.4896 | 0.8667 | 0.6154 |
pda | 0.8410(0.6760–1.000) | 0.8179 | 0.6392 | 0.8667 | 0.7692 |
knn | 0.6923(0.4882–0.8964) | 0.6795 | 0.3571 | 0.6667 | 0.6923 |
nnet | 0.7641(0.5781–0.9501) | 0.7564 | 0.5051 | 0.6667 | 0.8462 |