This repository was archived by the owner on Jan 6, 2022. It is now read-only.
Avoid saving big optimization path object #20
Description
When using mlrHyperopt very big objects get saved. This can be very annoying when doing repeated cross validation on several datasets, cause big objects are saved/used.
Example:
task = makeClassifTask(data = iris, target = "Species")
lrn = makeLearner("classif.svm")
lrn = makeHyperoptWrapper(lrn)
mod = train(lrn, task)
object.size(mod$learner.model$opt.result)
Is it possible to avoid this somehow?