rerf (version 2.0.4)

RunFeatureImportanceBinary: Compute Feature Importance of a single RerF tree

Description

Computes feature importance of every unique feature used to make a split in a single tree.

Usage

RunFeatureImportanceBinary(tree, unique.projections)

Arguments

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.

Value

feature.imp

Examples

# NOT RUN {
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)
# }