Use the relative variable importance chart to see which predictors
are the most important variables to the tree.
Relative variable importance standardizes the importance values for ease of
interpretation. Relative importance is defined as the percent improvement with
respect to the most important predictor.
An important variable is a variable that is used as a primary or surrogate
splitter in the tree. The variable with the highest improvement score is set as
the most important variable, and the other variables are ranked accordingly.
Relative variable importance standardizes the importance values for ease of
interpretation. Relative importance is defined as the percent improvement with
respect to the most important predictor.
Relative importance is calculated by dividing each variable importance
score by the largest importance score of the variables, then you multiply by
100%.
Interpretation
Relative variable importance values range from 0% to 100%. The most
important variable always has a relative importance of 100%. If a variable is
not used in the tree at all, it is not important.