Calculate which features the forest split on at each depth.

split_frequencies(forest, max.depth = 4)

Arguments

forest	The trained forest.
max.depth	Maximum depth of splits to consider.

Value

A matrix of split depth by feature index, where each value is the number of times the feature was split on at that depth.

Examples

# \donttest{
# Train a quantile forest.
n <- 250
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 split frequencies for this forest.
split_frequencies(q.forest)
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]  822  145  102  114  140  130  263   87  104    93
#> [2,]  897  337  313  344  343  329  361  281  315   294
#> [3,]  962  480  472  529  474  468  548  447  537   456
#> [4,]  910  552  550  590  576  537  600  519  594   528
# }