powered by
fit
evaluate.modeling
tune(proc, ..., .retune = FALSE, .verbose = FALSE)is.tuned(proc)is.tunable(proc)detune(proc)
is.tuned(proc)
is.tunable(proc)
detune(proc)
modeling.procedure
batch.model
Logical indicating if the procedure(s) are tuned.
Logical indicating if the has tunable parameters.
A list of untuned modeling procedures.
emil
predict
vimp
proc <- modeling.procedure("randomForest", param=list(mtry=1:4)) tuned.proc <- tune(proc, x=iris[-5], y=iris$Species) mod <- fit(tuned.proc, x=iris[-5], y=iris$Species)
Run the code above in your browser using DataLab