Merges a list of forests that were grown using the same data into one large forest.

merge_forests(forest_list, compute.oob.predictions = TRUE)

Arguments

forest_list	A `list` of forests to be concatenated. All forests must be of the same type, and the type must be a subclass of `grf`. In addition, all forests must have the same 'ci.group.size'. Other tuning parameters (e.g. alpha, mtry, min.node.size, imbalance.penalty) are allowed to differ across forests.
compute.oob.predictions	Whether OOB predictions on training set should be precomputed. Note that even if OOB predictions have already been precomputed for the forests in 'forest_list', those predictions are not used. Instead, a new set of oob predictions is computed anew using the larger forest. Default is TRUE.

Value

A single forest containing all the trees in each forest in the input list.

Examples

# \donttest{
# Train standard regression forests
n <- 50
p <- 10
X <- matrix(rnorm(n * p), n, p)
Y <- X[, 1] * rnorm(n)
r.forest1 <- regression_forest(X, Y, compute.oob.predictions = FALSE, num.trees = 100)
r.forest2 <- regression_forest(X, Y, compute.oob.predictions = FALSE, num.trees = 100)

# Join the forests together. The resulting forest will contain 200 trees.
big_rf <- merge_forests(list(r.forest1, r.forest2))
# }