better validation of inputs to Deconfounders

[raamana]

the #19 reminds me of how some users can be confused given the code lets the second argument to .fit() and .transform() optional with y=None. The only reason we have y=None is to try follow sklearn conventions and to pass their tests, but given we can't pass them anyway, we should tighten them up and make it an error to not supply the second [necessary] input argument.

cc @jrasero @jameschapman19