| Memory Allocation {party} | R Documentation |
This function sets up the memory needed for tree growing. It might be convenient to allocate memory only once but build multiple trees.
ctree_memory(object, MPinv = FALSE)
object |
an object of class LearningSample. |
MPinv |
a logical indicating whether memory for the Moore-Penrose inverse of covariance matrices should be allocated. |
This function is normally not to be called by users. However, for performance reasons it might be nice to allocate memory and re-fit trees using the same memory for the computations. Below is an example.
An object of class TreeFitMemory.
### setup learning sample
airq <- subset(airquality, !is.na(Ozone))
ls <- dpp(conditionalTree, Ozone ~ ., data = airq)
### setup memory and controls
mem <- ctree_memory(ls)
ct <- ctree_control(teststat = "max")
### fit 50 trees on bootstrap samples
bs <- rmultinom(50, nrow(airq), rep(1, nrow(airq))/nrow(airq))
storage.mode(bs) <- "double"
cfit <- conditionalTree@fit
system.time(ens <- apply(bs, 2, function(w) cfit(ls, ct, weights = w,
fitmem = mem)))