fig7

Figure 7. Decision tree visualization and feature importance of the best model (LGBM) based on all features in the modeling set. (A) shows a visualization for one of the 620 decision tree estimators in the developed LGBM model based on all features in the modeling set. In addition to showcasing the specific process of classification, the distribution ratio of samples is also displayed in each node and leaf, along with the data features and their corresponding thresholds upon which the classification is made; (B) displays the corresponding importance rank of each data feature based on the total gain of this feature's splits. LR_PO-UN, LR_FS-UN, and LR_2ND-UN are referred to as the LR value under hypotheses of PO-UN, FS-UN, and 2ND-UN. LR: Likelihood ratio; PO: parent-offspring; FS: full siblings; 2ND: 2nd-degree relatives; UN: unrelated individuals.