Memory Allocation {party} | R Documentation

## 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.

### 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.

### Value

An object of class `TreeFitMemory`.

### Examples

        ### 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)))

[Package party version 0.8-6 Index]