TABLE II.
Classifier | Augmented variables | Traditional variables | ||
---|---|---|---|---|
AUC | SD | AUC | SD | |
Random Forest | 0.826 | 0.010 | 0.774 | 0.012 |
Lasso | 0.810 | 0.011 | 0.780 | 0.012 |
Naïve bayes | 0.794 | 0.011 | 0.757 | 0.012 |
Neural nets | 0.772 | 0.012 | 0.481 | 0.014 |
kNN | 0.767 | 0.012 | 0.712 | 0.014 |
SVM | 0.761 | 0.011 | 0.667 | 0.013 |
Logistic regression | 0.563 | 0.053 | 0.727 | 0.014 |
Table II shows AUC and bootstrapped standard deviation of the tumor validation dataset for the best performing combination of tuning parameters and sampling techniques for each family of classifiers