A SEM Forest control object to tune parameters of the forest learning algorithm.
semforest.control(
num.trees = 5,
sampling = "subsample",
control = NA,
mtry = 2,
remove_dead_trees = TRUE
)
Number of trees.
Sampling procedure. Can be subsample or bootstrap.
A SEM Tree control object. Will be generated by default.
Number of subsampled covariates at each node.
Remove trees from forest that had runtime errors
Brandmaier, A.M., Oertzen, T. v., McArdle, J.J., & Lindenberger, U. (2013). Structural equation model trees. Psychological Methods, 18(1), 71-86.