cforest: Conditional Random Forests See '?partykit::cforest'.

In difuture-lmu/rmmodeldata: Remove data from models

Conditional Random Forests See ?partykit::cforest.

Description

Conditional Random Forests See ?partykit::cforest.

Usage

cforest(
  formula,
  data,
  weights,
  subset,
  offset,
  cluster,
  strata,
  na.action = na.pass,
  control = partykit::ctree_control(teststat = "quad", testtype = "Univ", mincriterion
    = 0, saveinfo = FALSE, ...),
  ytrafo = NULL,
  scores = NULL,
  ntree = 500L,
  perturb = list(replace = FALSE, fraction = 0.632),
  mtry = ceiling(sqrt(nvar)),
  applyfun = NULL,
  cores = NULL,
  trace = FALSE,
  ...
)

Arguments

formula	(see ?partykit::cforest)
data	(see ?partykit::cforest)
weights	(see ?partykit::cforest)
subset	(see ?partykit::cforest)
offset	(see ?partykit::cforest)
cluster	(see ?partykit::cforest)
strata	(see ?partykit::cforest)
na.action	(see ?partykit::cforest)
control	(see ?partykit::cforest)
ytrafo	(see ?partykit::cforest)
scores	(see ?partykit::cforest)
ntree	(see ?partykit::cforest)
perturb	(see ?partykit::cforest)
mtry	(see ?partykit::cforest)
applyfun	(see ?partykit::cforest)
cores	(see ?partykit::cforest)
trace	(see ?partykit::cforest)
...	(see ?partykit::cforest)

difuture-lmu/rmmodeldata documentation built on July 14, 2022, 4:49 a.m.