party (version 0.2-3)

Memory Allocation: Memory Allocation

Description

This function sets up the memory needed for tree growing. It might be convenient to allocate memory only once but build multiple trees.

Usage

ctree_memory(object, MPinv = FALSE)

Arguments

object
an object of class LearningSample.
MPinv
a logical indicating whether memory for the Moore-Penrose inverse of covariance matrices should be allocated.

Value

  • An object of class TreeFitMemory.

Details

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.

Examples

Run this code
### setup learning sample
    data(airquality)
    airq <- subset(airquality, !is.na(Ozone))
    ls <- dpp(conditionalTree, Ozone ~ ., data = airq)

    ### setup memory and controls 
    mem <- ctree_memory(ls)
    ct <- ctree_control(teststattype = "maxabs")

    ### 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)))

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