lrn = makeLearner("classif.logreg")
cpolrn = cpoScale() %>>% lrn
print(cpolrn)
getLearnerBare(cpolrn) # classif.logreg Learner
getLearnerCPO(cpolrn) # cpoScale() CPO
getParamSet(cpolrn) # includes cpoScale hyperparameters
model = train(cpolrn, pid.task) # behaves like a learner
retrafo(model) # the CPORetrafo that was trained
predict(model, pid.task) # otherwise behaves like an mlr model
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