This would be interesting and a good addition I think.
It bears some thought about the API though. One approach is to have an "inverseTransform" method similar to sklearn.
The other approach is to "formalize" something like StringIndexerModel -> IndexToString. Here, the inverse transformer is a standalone transformer. It could be returned from a "getInverseTransformer" method, for example.
The former approach is simpler, but cannot be used in pipelines (which work on "fit" / "transform"). The latter approach is more cumbersome, but fits better into pipelines.
So it depends on the use cases - i.e. how common is it to use the inverse transform function within a pipeline (for StringIndexer <-> IndexToString it is quite common to get back the labels, while for other transformers it may or may not be).
After traning MinMaxScaler(or similar scaler) is there any built-in way to revert the process? What I mean is to transform the scaled data back to its original form. SKlearn has a dedicated method inverse_transform that does exactly that.
I can, of course, get the originalMin/originalMax Vectors from the MinMaxScalerModel and then map the values myself but it would be nice to have it built-in.