Fig. 4
From: A top-down supervised learning approach to hierarchical multi-label classification in networks
Prediction performance of the hierarchical multi-label classification approach with XGBoost (XGB) and graph convolutional network (GraphCN) classifiers, and the probabilistic model (HBN) for the 15 sub-hierarchies of Oriza sativa Japonica. Performance is measured with area under the ROC curve and the average precision score. Note that the notation used for the graph convolutional network is GraphCN to distinguish it from the gene co-expression network (GCN)