Description Usage Arguments Value References See Also Examples
Computes local or aggregate variable importance for a set of predictors from a fitted random forest object from the party, randomForest, randomForestSRC, or ranger package
1 | variable_importance(fit, vars, interaction, nperm, data, ...)
|
fit |
object of class 'RandomForest', 'randomForest', 'rfsrc', or 'ranger' |
vars |
character, variables to find the importance of |
interaction |
logcal, compute the joint and additive importance for observations ( |
nperm |
positive integer giving the number of times to permute the indicated variables (default 10) |
data |
optional (unless using randomForest) data.frame with which to calculate importance |
... |
additional arguments to be passed to |
a named list of vars
with the return from permutationImportance
for each.
Breiman, Leo. "Random forests." Machine learning 45.1 (2001): 5-32.
plot_imp
for plotting the results of variable_importance
.
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