Protein Remote Homology Detection Based on an Ensemble Learning Approach

Table 4

Performance comparison of different methods on the benchmark dataset.

Methods	ROC	ROC50	Source
SVM-Ensemble	0.943	0.744	This study
SVM-Pairwise	0.896	0.464	Liao and Noble, 2003 [5]
SVM-LA ()	0.925	0.649	Saigo et al., 2004 [26]
Mismatch	0.925	0.649	Leslie et al., 2004 [28]
Monomer-dist	0.919	0.508	Lingner and Meinicke, 2006 [47]
SVM-WCM	0.904	0.445	Lingner and Meinicke, 2008 [51]
SVM-Ngram-LSA	0.859	0.628	Dong et al., 2006 [48]
SVM-Pattern-LSA	0.879	0.626	Dong et al., 2006 [48]
SVM-Motif-LSA	0.859	0.628	Dong et al., 2006 [48]
SVM-Top-n-gram-combine-LSA	0.939	0.767	Liu et al., 2008 [4]
PseAACIndex ()	0.880	0.620	Liu et al., 2013 [31, 52]
PseAACIndex-Profile ()	0.922	0.712	Liu et al., 2013 [31, 52]
SVM-DR	0.919	0.715	Liu et al., 2014 [50, 53–55]
disPseAAC	0.922	0.721	Liu et al., 2015 [2, 32, 44, 45, 56–59]

Average ROC and ROC50 scores.