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Table 1 Results for multi-class superfamily prediction in the remote homology detection set-up. Results for the adaptive codes method are reported for a SCOP benchmark data set (67 folds, 74 superfamilies, 544 families, with 802 test sequences).

From: SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

Method (and optimization target) Error Balanced Error Top 5 Error Balanced Top 5 Error Detection Rate at fdr = 1% Detection Rate at fdr = 5%
PSI-BLAST 0.3990 0.4571 0.2731 0.3654 0.3229 0.4214
one-vs-all: Sfams 0.2706 0.4454 0.1047 0.1973 0.4239 0.5549
one-vs-all: Sfams, Fams 0.2706 0.4454 0.1097 0.2070 0.4239 0.5549
Sigmoid Fitting: Sfams 0.3678 0.5561 0.2020 0.3724 0.3641 0.4726
Adaptive Codes: Sfams (zero-one) 0.2444 0.3805 0.0960 0.1591 0.4264 0.5711
Adaptive Codes: Sfams (balanced) 0.2481 0.3723 0.1110 0.1634 0.4289 0.5673
Adaptive Codes: Sfams, Fams (zero-one) 0.2369 0.3739 0.0948 0.1561 0.4352 0.5698
Adaptive Codes: Sfams, Fams (balanced) 0.2394 0.3632 0.1047 0.1558 0.4302 0.5698
Adaptive Codes: Sfams, Fams, Fams (zero-one) 0.2219 0.3401 0.0910 0.1359 0.4277 0.5723
Adaptive Codes: Sfams, Fams, Fams (balanced) 0.2195 0.3273 0.1047 0.1516 0.4327 0.5910