Table 3

Summary of classification performance for the Vote Threshold aggregation method
VOTE THRESHOLD Sensitivity Specificity AUC
Ensemble classifier Individual classifiers Ensemble classifier Individual classifiers Ensemble classifier Individual classifiers
min max average min max average min max average
Ensemble 1 0.82 0.64 0.73 0.68 0.86 0.90 0.95 0.93 0.89 0.73 0.94 0.84
Ensemble 2 0.91 0.55 0.82 0.69 0.76 0.86 1.00 0.93 0.89 0.73 0.96 0.88
Ensemble 3 1.00 0.64 0.73 0.65 0.76 0.81 0.95 0.91 0.90 0.73 0.94 0.88
Ensemble 4 0.91 0.55 0.73 0.64 0.81 0.81 1.00 0.92 0.95 0.83 0.95 0.90
Ensemble 5 1.00 0.55 0.82 0.66 0.62 0.81 1.00 0.92 0.90 0.73 0.96 0.89

Shown is classification performance for the 5 ensembles defined in Table 1 when using the vote threshold aggregation method. Similarly to Table 2, individual classifier performances are included for comparison.

Günther et al.

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

Open Data