Yes it is; and you are correct, it's not necessarily trivial; but the point I'm making isn't about reducing very high dimension inputs into lower dimension outp

Yes it is; and you are correct, it's not necessarily trivial; but the point I'm making isn't about reducing very high dimension inputs into lower dimension outputs or picking the best function to map between data sets. ...how you implement those functions, how you optimise for the best results and performance is an implementation detail. If you are picking your solution before you know what your problem is, you are falling into premature optimisation. Understanding how to reduce your problem domain into a series of functions that take numerical data and return numeric data is the key practical problem that most people face, and it's poorly described in the literature. (That's why most people just pull out that classic line '...its great for image recognition and ...many other things...')