Skip to main content

Table 5 Summary of classification performance for the Average Probability aggregation method

From: A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers

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 A

1.0000

0.9211

0.9737

0.9474

0.8421

0.8421

0.8421

0.8421

0.9972

0.9626

0.9737

0.9681

Ensemble B

0.9737

0.9211

0.9211

0.9211

0.8421

0.8421

0.8421

0.8421

0.9931

0.9557

0.9612

0.9584

Ensemble C

1.0000

0.9211

0.9737

0.9539

0.8421

0.7368

0.8947

0.8421

0.9917

0.9501

0.9709

0.9602

Ensemble D

1.0000

0.9211

0.9737

0.9386

0.9474

0.8421

0.9474

0.9035

0.9986

0.9557

0.9778

0.9677

Ensemble E

1.0000

0.8947

1.0000

0.9518

0.8947

0.7368

0.9474

0.8553

0.9972

0.9418

0.9765

0.9643

Ensemble F

1.0000

0.9211

0.9737

0.9430

0.9474

0.8421

0.9474

0.8816

0.9986

0.9557

0.9848

0.9672

  1. Shown is performance for tumour vs normal classification for the 6 ensembles defined in Table 4 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.