Table 2

Summary of classification performance for the Average Probability aggregation method
AVERAGE PROBABILITY 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 0.73 0.64 0.73 0.68 0.90 0.90 0.95 0.93 0.95 0.73 0.94 0.84
Ensemble 2 0.82 0.55 0.82 0.69 0.95 0.86 1.00 0.93 0.98 0.73 0.96 0.88
Ensemble 3 0.73 0.64 0.73 0.65 0.95 0.81 0.95 0.91 0.97 0.73 0.94 0.88
Ensemble 4 0.82 0.55 0.73 0.64 0.90 0.81 1.00 0.92 0.97 0.83 0.95 0.90
Ensemble 5 0.82 0.55 0.82 0.66 0.95 0.81 1.00 0.92 0.98 0.73 0.96 0.89

Shown is classification performance as measured by sensitivity, specificity and AUC – for the 5 ensembles defined in Table 1 when using the average probability aggregation method. The minimum, maximum and average performances of individual classifiers in the respective ensemble are included in the table for comparison.

Günther et al.

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

Open Data