text: Title: eventually, train on the entire dataset even when warm_starting, or early_stopping
  Body: right now we're losing 10-15% of our data for our validation stuff, to find the best number of rounds/iterations/estimators/etc. 
  
  eventually, it would be ideal to train with early stopping to find the ideal number of iterations, then use that (plus some small amount, say 5% of however many num_iteration we have to account for the fact that we'll have a slightly larger dataset now) to train a new model with all the data. 
  
  so, we'd end up training the model twice: once to find the ideal num_iteration, once with the full dataset using the ideal num_iteration. 
  
  make this a param to .train(). not sure of the name yet. 