Predicting Disease-Gene Associations using Cross-Document Graph-based Features
Table 1: Evaluation results of classification models based on indiviudal feature groups (left) and feature group combinations (right) on GTR testing data
['[BOLD] Feat.\xa0Combination', '[BOLD] Prec.', '[BOLD] Rec.', 'F1']
The left part displays classification performance of individudal feature groups; in the right part, testing performance of feature combinations (as selected by cross-validation on the training data) are shown.