For a ML library, which would be the arguments in favour to use a new specific function name for the inverse prediction for a model (e.g. a zero-mean/unit variance scaler), something like inversePrediction(mod,Xnew), and which arguments would be in favour to just use a keyword argument to the already employed predict function, something like predict(mod,Xnew;inv=true) ?
Some context:
- I use only
predict(mod)(and eventuallypredict(mod,Xnew)for models that generalise to new data) for unsupervised models and so-called transformers without distinguishing between them - I use camel case
- MLJ and scikit-learn use
inverse_transform - I care more to user-friendly than performance