Figure 5
From: Multidimensional variability in ecological assessments predicts two clusters of suicidal patients
Importance of the ten clinical and demographic features used by the random forest to automatically discriminate patients in the low- and high-variability groups. For clarity, the y-axis is sorted in increasing importance order according to the random forest. The importance is computed by summing all changes in the impurity of the nodes from the parent to the two children thanks to a given clinical feature and its corresponding surrogate splits. Impurity is a measure of how the decisions of a node can separate patients in the low- and high-variability groups and it is measured by the Gini’s diversity index. The sum of impurity changes is normalized by the number of branch nodes.
