Figure 7
From: Glycosylation site prediction using ensembles of Support Vector Machine classifiers
Architecture of the ensemble of Support Vector Machine classifiers. A collection of m SVM classifiers, each trained on a balanced subsample of the training data (approximately equal number of positive and negative instances obtained by sampling with replacement from the entire training data). The ensemble of SVM classifiers is trained and evaluated on the original distribution of the glycosylation data. The prediction of the ensemble of SVMs is computed from the predictions of the individual SVM classifiers.