Table 4. Cytotoxic T cell signature training set prediction.
AUC | Sens | Spec | AUCSD | SensSD | SpecSD | Model |
---|---|---|---|---|---|---|
0.681 | 0.603 | 0.737 | 0.064 | 0.155 | 0.149 | Random forest |
0.674 | 0.604 | 0.665 | 0.076 | 0.144 | 0.088 | Penalized discriminant analysis |
0.647 | 0.597 | 0.717 | 0.052 | 0.130 | 0.144 | Bagged CART |
0.628 | 0.616 | 0.677 | 0.074 | 0.117 | 0.113 | Penalized logistic regression |
0.622 | 0.472 | 0.696 | 0.099 | 0.123 | 0.137 | CART |
0.607 | 0.579 | 0.586 | 0.075 | 0.121 | 0.121 | Sparse discriminant analysis |
0.574 | 0.515 | 0.625 | 0.249 | 0.302 | 0.246 | Linear discriminant |
0.545 | 0.420 | 0.545 | 0.167 | 0.242 | 0.222 | Naive Bayes |
AUC, area under the curve; Sens, sensitivity; Spec, specificity; AUCSD, area under the curve standard deviation; SensSD, sensitivity standard deviation; SpecSD, specificity standard deviation; CART, classification and regression tree