Embedded Methods
We trained two classifiers with the underlying algorithms SVM and GLMNET
(see Table 1). Both algorithms achieved 100% accuracy (ACC) on the test
set, with a 95% likelihood that the true value lies between (54% -
100%); the wide range is due to the limited size of the test set. The
No Information Rate (NIR) was 0.5, as we started from a balanced
dataset, and the p-value for ACC > NIR was 0.01563. We
concluded that both algorithms generalised successfully, as high
performance was achieved on both the training and test datasets (see
also Supplemental Information).