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,] 735 137 127 138 176 128 250 104 92 113 #> [2,] 868 345 303 300 313 350 353 280 299 328 #> [3,] 951 507 523 494 506 560 534 460 472 499 #> [4,] 987 546 677 575 585 591 568 556 581 608
# }