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. 2008 Mar 4;24(8):1049–1055. doi: 10.1093/bioinformatics/btn084

Fig. 2.

Fig. 2.

Comparison between RF and SVM classifiers specialized in ‘new’ sites, and the effect of the furin correction factor. VALIDATED and POTENTIAL data are treated as positive for testing, the rest as negative. The furin correction is a way to compensate for the fact that some of the data we treated as negative for cleavage is actually mislabeled (unknown proteolytic sites). (A) Raw score output of the RF and SVM classifiers; (B) Precision is multiplied by 3.04, which is the calculated furin correction factor. It should be remarked that because of the imperfection of the correction procedure, corrected precision values may exceed 1. Precision values that exceed 1 are set to 1.