text: Title: How are samples generated with RegressionModel / MLPRegressor?
  Body: Hi there,
  
  I tried sklearn's `MLPRegressor` with the `RegressionModel` wrapper, and to my surprise, I was able to generate samples with `historical_forecasts` (e.g. with `num_samples = 1000`). How is this possible? Neither `RegressionModel` nor `MLPRegressor` accepts any kind of likelihood or loss function as an argument or am I missing something? 
  
  `model.supports_probabilistic_prediction` is actually false in my case but I can still generate samples.
  
  I would be happy to use this but it is not officially supported, right?
  