grf (version 0.9.5)

variable_importance: Calculate a simple measure of 'importance' for each feature.

Description

Calculate a simple measure of 'importance' for each feature.

Usage

variable_importance(forest, decay.exponent = 2, max.depth = 4)

Arguments

forest

The trained forest.

decay.exponent

A tuning parameter that controls the importance of split depth.

max.depth

Maximum depth of splits to consider.

Value

A list specifying an 'importance value' for each feature.

Examples

# NOT RUN {
# Train a quantile forest.
n = 50; p = 10
X = matrix(rnorm(n*p), n, p)
Y = X[,1] * rnorm(n)
q.forest = quantile_forest(X, Y, quantiles=c(0.1, 0.5, 0.9))

# Calculate the 'importance' of each feature.
variable_importance(q.forest)
# }
# NOT RUN {
# }