Sorry for the bad title, I can't find a good one. So I will try to explain what I'm looking for.
I'm doing sales forecasting with a Regression Forest. (Spark - Scala for the technology) I've worked on some test data and I did my forecast using training data. But some of the features which I have used can't be employed to forecast the future as they would not be known to me at any given time. For example the numbers of customers of a day, their categories, what kind of advantage they have etc.
Do I have to find others features that will be as useful as these ones or Do I need to perform prediction on these features before my sales forecasting and use the predictions? Are there any another solutions? Also, what kind of algorithms should I use for the "features forecasting"?