Table 3 Comparison of performances (precisions) of Random Forest (RF) and k-Nearest Neighbors (k-NN) classifiers with performances of other methods in published works ([75, 76]) over the same datasets. SM is the single model method; AVG considers the average of the likelihood scores given by the models inferred from five different perturbation random seeds; ∩_x/5 considers those predictions from x out of the five models. For RF and k-NN evaluations, probability of perturbation p and likelihood threshold ρ were set to their respective default values p=10% and ρ=0.8

From: Gene function finding through cross-organism ensemble learning