Broadcasting probabilistic Unaggregated measures (such as proper scoring rules) over a single prediction

[ablaom]

The idea of implementing "distribution fitters" as supervised models is to enable their evaluation using a proper scoring rule (which in turn makes hyper-parameter optimization possible).

There are precisely zero models implementing this API, but as currently specified, predict(mach, nothing) returns the fitted distribution. Now to evaluate using some examples using, say, log_score, we need a broadcast version of log_score(yhat, y) where yhat is a single distribution and y a number of observations (samples). Currently measures expect yhat and y to be arrays of the same dimension.