Table 4

Performance comparison between J48 and decision tree based ensembles

Method

Sensitivity

Specificity

F-Measure

Accuracy

AUC


J48

0.858

0.843

0.850

0.850

0.892

AdaBoost

0.890

0.910

0.902

0.900

0.932

Bagging

0.870

0.872

0.873

0.871

0.940

MultiBoost

0.880

0.871

0.876

0.876

0.942

Random Forest

0.819

0.889

0.859

0.850

0.908


The ensemble classifiers include bagging, AdaBoost, MultiBoost, random forest.

Che et al. BMC Genomics 2010 11(Suppl 2):S1   doi:10.1186/1471-2164-11-S2-S1

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