Random Forest prediction via predict.ranger. Predicts response variables
from predictor variables, using ranger objects. All ranger objects have to work
on the same set of prediction variables. These variables are exactly available in the
prediction dataset. A response is not necessary, it will be predicted via this function.
randomForestPredict(
dataset = cs.in.dataset(),
preds = cs.in.predictors(),
robject = cs.in.Robject(),
return.results = FALSE,
...
)[data.frame]
Dataset with named columns. The names correspond to predictors and responses.
[character]
Character vector of predictor variables.
[list]
Named list of
ranger
object(s) set via Cornerstone menu "Input R Objects".
[logical(1)]
If FALSE the function returns TRUE invisibly.
If TRUE, it returns a list of results.
Default is FALSE.
[ANY]
Additional arguments to be passed to
ranger
. Please consider possible script variables (scriptvars) to prevent duplicates.
Logical [TRUE] invisibly and outputs to Cornerstone or,
if return.results = TRUE, list of
resulting data.frame objects:
Dataset to brush with predicted values for dataset. The original input and other
columns can be added to this dataset through the menu Columns -> Add from Parent ....