Classification accuracy of five different machine-learning methods used for classification of HNSCC vs. SQCLC. SVM, Support Vector Machine with a linear kernel; RPART, Classification and Regression Tree (CART); NB, naïve Bayes classifier; PAM, Partitioning Around Medoids / Nearest Shrunken Centroids; PLR, L1-Penalised Logistic Regression. All models were fitted by using the R/Bioconductor package 'caret'. Model hyperparameters were optimised by using caret's tuning option; accuracies were computed by bootstrapping with 25 repetitions, shown are mean accuracy ± standard deviation. 