View source: R/forest.wrapper.R
| vt.forest | R Documentation | 
vt.forest is a wrapper of VT.forest.one, 
VT.forest.double and VT.forest.fold. With 
parameter forest.type, any of these class can be used with its own parameter.
vt.forest(forest.type = "one", vt.data, interactions = T,
  method = "absolute", model = NULL, model_trt1 = NULL,
  model_trt0 = NULL, ratio = 1, fold = 10, ...)
forest.type | 
 must be a character. "one" to use VT.forest.one class. "double" to use VT.forest.double. "fold" to use VT.forest.fold.  | 
vt.data | 
 
  | 
interactions | 
 logical. If running VirtualTwins with treatment's interactions, set to TRUE (default value)  | 
method | 
 character c("absolute", "relative", "logit"). See 
  | 
model | 
 allows to give a model you build outside this function. Can be randomForest, train or cforest. Is only used with forest.type = "one". If NULL, a randomForest model is grown inside the function. NULL is default.  | 
model_trt1 | 
 see model_trt0 explanation and 
  | 
model_trt0 | 
 works the same as model parameter. Is only used with 
forest.type = "double". If NULL, a randomForest model is grown inside the 
function. NULL is default. See   | 
ratio | 
 numeric value that allow sampsize to be a bit controlled.
Default to 1. See   | 
fold | 
 number of fold you want to construct forest with k-fold method. 
Is only used with forest.type = "fold". Default to 5. See 
  | 
... | 
 randomForest() function parameters. Can be used for any forest.type.  | 
VT.difft
data(sepsis)
vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
# inside model :
vt.f <- vt.forest("one", vt.o)
# ...
# your model :
# library(randomForest)
# rf <- randomForest(y = vt.o$getY(),
#                    x = vt.o$getX(int = T),
#                    mtry = 3,
#                    nodesize = 15)
# vt.f <- vt.forest("one", vt.o, model = rf)
# ...
# Can also use ... parameters
vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
# ...
   
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