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Table 4 Performance comparison between J48 and decision tree based ensembles

From: Classification of genomic islands using decision trees and their ensemble algorithms

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