Description Usage Arguments Value Examples
View source: R/RunFeatureImportance.R
Computes feature importance of every unique feature used to make a split in a single tree.
1 | RunFeatureImportanceBinary(tree, unique.projections)
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tree |
a single tree from a trained RerF model with argument store.impurity = TRUE. |
unique.projections |
a list of all of the unique split projections used in the RerF model. |
feature.imp
1 2 3 4 5 6 7 | library(rerf)
X <- iris[, -5]
Y <- iris[[5]]
store.impurity <- TRUE
FUN <- RandMatBinary
forest <- RerF(X, Y, FUN = FUN, num.cores = 1L, store.impurity = store.impurity)
FeatureImportance(forest, num.cores = 1L)
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