Criteria | Linear Discriminant Analysis | General Linear Model | Multinomial Logistic Regession | ||||||
---|---|---|---|---|---|---|---|---|---|
 | No 4's Attn | CPT-II Attn | Activity | No 4's Attn | CPT-II Attn | Activity | No 4's Attn | CPT-II Attn | Activity |
Accuracy | 0.659 | 0.670 | 0.768ab | 0.650 | 0.663 | 0.766ab | 0.703 | 0.706 | 0.801ab |
Kappa | 0.257 | 0.281 | 0.505ab | 0.240 | 0.269 | 0.504ab | 0.360 | 0.360 | 0.583ab |
ROC-AUC | 0.671 | 0.712 | 0.821ab | 0.661 | 0.692 | 0.800ab | 0.722 | 0.729 | 0.839ab |
Sensitivity | 0.786 | 0.790 | 0.835cd | 0.752 | 0.776 | 0.816ef | 0.800 | 0.821 | 0.829 |
Specificity | 0.462 | 0.482 | 0.665ab | 0.491 | 0.486 | 0.687ab | 0.552 | 0.528 | 0.758ab |
Criteria | Neural Network | Support Vector Machine | Random Forest Classification | ||||||
 | No 4's Attn | CPT-II Attn | Activity | No 4's Attn | CPT-II Attn | Activity | No 4's Attn | CPT-II Attn | Activity |
Accuracy | 0.659 | 0.677 | 0.809ab | 0.720 | 0.709 | 0.817ab | 0.663 | 0.624 | 0.842ab |
Kappa | 0.273 | 0.299 | 0.607ab | 0.396 | 0.376 | 0.621ab | 0.292 | 0.191 | 0.676ab |
ROC-AUC | 0.687 | 0.711 | 0.816ab | 0.731 | 0.753 | 0.829ab | 0.661 | 0.673 | 0.889ab |
Sensitivity | 0.742 | 0.769 | 0.801ab | 0.811 | 0.793 | 0.807 | 0.753 | 0.775 | 0.828ab |
Specificity | 0.528 | 0.534 | 0.802ab | 0.578 | 0.578 | 0.833ab | 0.543 | 0.415 | 0.870ab |