Skip to main content
Fig. 2 | BioData Mining

Fig. 2

From: Gene function finding through cross-organism ensemble learning

Fig. 2

Evaluation results by varying the perturbation percentage. Results obtained by varying the perturbation percentage of the Homosapiens training annotation matrix and using Random Forest as supervised algorithm and the likelihood threshold ρ=0.8. SM is the single model method, proposed in [57]; AVG considers the average of the likelihood scores given by the models inferred from five different perturbation random seeds; ∩1/5 considers the union of the predictions from the five models; ∩5/5 considers the intersection of the predictions from the five models; ∩3/5 considers those predictions from three out of the five models

Back to article page
\