Fig. 4

Performance of GWAVA, CERENKOV and CERENKOV2 on the OSU18 reference SNP set, by three performance measures. Marks, sample arithmetic mean of validation-set performance; bars, estimated 95% confidence intervals (see “Gradient boosted decision trees” section); GWAVA, based on the GWAVA’s Random Forest model with 174 features [24]; CERENKOV, our previous model with the base 248-column feature matrix; CERENKOV2, our current model consisting of the base feature matrix plus ten log-likelihood features derived from intralocus radii and fitted using training data only; AUPVR, area under the precision-vs-recall curve (higher is better); AUROC, area under the receiver operating characteristic curve (higher is better); AVGRANK, intralocus average score rank (lower is better [22])