CPO Learners are created when a CPO
gets attached to an mlr-Learner
object. The resulting
learner performs the operation described by the attached CPO
before fitting the model specified by the
Learner
. It is possible to attach compound CPOs, and it is possible to attach more CPOs to a learner
that is already a CPOLearner
. If the attached CPO exports hyperparameters, these become part of the newly created
learner and can be queried and set using functions such as getParamSet
, getHyperPars
,
and setHyperPars
.
The model created when training a CPOLearner
also contains the relevant CPORetrafo
information to be applied
to prediction data; this can be retrieved using retrafo
. The CPOInverter
functionality is handled
equally transparently by the model.
A CPOLearner can possibly have different LearnerProperties
than the base Learner
to which
it is attached. This depends on the CPO
's properties, see CPOProperties
.
It is possible to retrieve the CPOLearner
's base learner using getLearnerBare
, and to get the attached CPOs
using getLearnerCPO
.