Table 4

Overview of individual classifier performance and definition of ensembles
Classifier Method Features Accuracy Sensitivity Specificity AUC Ensemble A Ensemble B Ensemble C Ensemble D Ensemble E Ensemble F
mRNA-Classifier1 EN 182 0.9298 0.9737 0.8421 0.9737 X X X
mRNA-Classifier2 EN 73 0.9123 1.0000 0.7368 0.9709 X
mRNA-Classifier3 EN 36 0.8947 0.9737 0.7368 0.9501 X X
mRNA-Classifier4 LDA 2 0.9298 0.9211 0.9474 0.9640 X
mRNA-Classifier5 RF 500 0.8947 0.9737 0.7368 0.9418 X
mRNA-Classifier6 SVM 500 0.9298 0.9474 0.8947 0.9640 X
mRNA-Classifier7 EN 43 0.9123 0.9474 0.8421 0.9598 X
mRNA-Classifier8 EN 25 0.9298 0.9737 0.8421 0.9612 X
mRNA-Classifier9 EN 17 0.9298 0.9737 0.8421 0.9695 X
mRNA-Classifier10 LDA 2 0.9298 0.9211 0.9474 0.9640 X X
mRNA-Classifier11 RF 50 0.9298 0.9474 0.8947 0.9584 X X
mRNA-Classifier12 SVM 50 0.8947 0.9211 0.8421 0.9557 X X X
miRNA-Classifier1 EN 66 0.8947 0.9211 0.8421 0.9626 X X
miRNA-Classifier2 EN 21 0.9474 0.9737 0.8947 0.9709 X X
miRNA-Classifier3 EN 8 0.9649 0.9737 0.9474 0.9723 X X
miRNA-Classifier4 LDA 4 0.9298 0.9211 0.9474 0.9626 X X
miRNA-Classifier5 RF 152 0.8947 0.8947 0.8947 0.9765 X
miRNA-Classifier6 SVM 152 0.9123 0.9474 0.8421 0.9626 X
miRNA-Classifier7 EN 36 0.9298 0.9474 0.8947 0.9709 X
miRNA-Classifier8 EN 16 0.9298 0.9474 0.8947 0.9848 X
miRNA-Classifier9 EN 12 0.9474 0.9737 0.8947 0.9806 X
miRNA-Classifier10 LDA 4 0.9298 0.9211 0.9474 0.9626 X
miRNA-Classifier11 RF 50 0.9123 0.9211 0.8947 0.9778 X X
miRNA-Classifier12 SVM 50 0.8947 0.9211 0.8421 0.9612 X X X

Shown is a list of 12 mRNA- and 12 miRNA classifiers, their individual classification performance and their inclusion into 6 ensembles that are explored for classification of tumour vs normal samples. Abbreviations are the same as in Table 1.

Günther et al.

Günther et al. BMC Bioinformatics 2012 13:326   doi:10.1186/1471-2105-13-326

Open Data