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mlr

Is there any function to make complex learner in MLR

I'm currently learning the MLR package. MLR provide function to enhance the power of base learner. Like makePreprocWrapperCaret for data preprocessing, makeFilterWrapperfor feature selection. I'm wondering if there are any more flexible functions, that can allow the merge of complex processing in one learner, like first scaling the data, then feature selection, and finally tune the data. Or I have to write my custom learner function to achieve this?

Solution

  • You can easily do this by layering multiple wrappers. For more information on wrappers, see the relevant part of the tutorial.