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@AnnaNzrv AnnaNzrv commented Sep 13, 2025

This pr implements a novel base class for Python based learners.

Open ToDo's:

  • Marshaling works
  • Encapsulation works
  • Refactor all python-based learners
  • Update tutorial to include this new class
  • Extend implementation to regression learners

structure(
list(
fitted = fit$model, # PyObject
meta = meta, # any R metadata (e.g., classes)
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Add the elements of meta directly to the returned list.

class_labels = task$class_names
)

if ("prob" %in% self$predict_types && !is.null(res$prob)) {
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This is also handled in mlr3. Take a look at the other learners.

@be-marc
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be-marc commented Sep 22, 2025

When you are finished with this, you can add a helper function for converting config space objects from python to paradox in R.

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3 participants