Protein Remote Homology Detection Based on an Ensemble Learning Approach

Table 2

Performance of ensemble classifier combining various predictors with weighted voting. The best performance was achieved by combining SVM-Kmer, SVM-ACC, and SVM-SC-PseAAC. The symbol denotes the weighted voting operator.

Ensemble methods with superfamily-level strategy	ROC	ROC50
SVM-Kmer SVM-ACC	0.929	0.767
SVM-Kmer SVM-SC-PseAAC	0.937	0.715
SVM-ACC SVM-SC-PseAAC	0.922	0.691
SVM-Kmer SVM-ACC SVM-SC-PseAAC	0.943	0.744

Average ROC and ROC50 scores.