R Under development (unstable) (2025-12-15 r89175 ucrt) -- "Unsuffered Consequences"
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> suppressMessages(library("wsrf"))
> suppressMessages(library("randomForest"))
> 
> # prepare parameters
> ds <- iris
> target <- "Species"
> vars <- names(ds)
> if (sum(is.na(ds[vars]))) ds[vars] <- na.roughfix(ds[vars])
> ds[target] <- as.factor(ds[[target]])
> (form <- as.formula(paste(target, "~ .")))
Species ~ .
> set.seed(500)
> length(train <- sample(nrow(ds), 0.7*nrow(ds)))
[1] 105
> length(test  <- setdiff(seq_len(nrow(ds)), train))
[1] 45
> 
> 
> # build model
> model.wsrf       <- wsrf(form, data=ds[train, vars], parallel=FALSE)
> model.wsrf.nw    <- wsrf(form, data=ds[train, vars], weights=FALSE, parallel=FALSE)
> model.wsrf.nw.vi <- wsrf(form, data=ds[train, vars], weights=FALSE, importance=TRUE, parallel=FALSE)
> model.subset     <- subset.wsrf(model.wsrf, 1:200)
> model.combine    <- combine.wsrf(model.wsrf, model.wsrf.nw)
> 
> 
> # evaluate
> 
> # Note:
> # 32bit system and 64bit system will have different results, however,
> # if random seed is fixed, the same results will be presented in the
> # same system.
> 
> cl         <- predict(model.wsrf,     newdata=ds[test, vars], type="class")$class
> cl.nw      <- predict(model.wsrf.nw,  newdata=ds[test, vars], type="class")$class
> cl.subset  <- predict(model.subset,   newdata=ds[test, vars], type="class")$class
> cl.combine <- predict(model.combine,  newdata=ds[test, vars], type="class")$class
> 
> proc.time()
   user  system elapsed 
   0.39    0.06    0.42