Fig. 3
From: Identifying relapse predictors in individual participant data with decision trees
Decision tree feature importance. a Feature importance (i.e., the relative frequency at which a certain feature occurs in a trained decision-tree classifier) associated with a decision tree with a depth of three. b Feature importance associated with a gradient-boosted tree of depth one. The shown results are based on 1000 cross-validation realizations. The training dataset consist of 380 samples. In both box plots, red lines show the median feature importance. Outliers are represented by black circles