Additional file 5: Figure S4. of A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma

Abstract

Cohen’s D effect size estimates across five fold cross validation parameters for all 100 iterations of the TDM transformed ensemble classifier. The effect size for the test set is consistently lower than the training set (left). Additionally, the training and testing decision functions for gold standard NF1 deficient vs. NF1 wildtype samples shows a difference in mean estimates (right). The decision function represents the raw score of all samples as applied to the respective classifiers through each of the 100 iterations of five fold cross validation on the TCGA training set. (PNG 580 kb