CPO object can be attached to a
Learner object to create a
pipeline combining preprocessing and model fitting. When the resulting
is used to create a model using
train, the attached CPO will be applied to the
data before the internal model is trained. The resulting model will also contain the required
CPOTrained elements, and apply the necessary
CPORetrafo objects to new prediction
data, and the
CPOInverter objects to predictions made by the internal model.
%>>% operator can be used synonymously to attach CPO objects to Learners.
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