BUG: Fix performance regression on large datasets in random forest.
The crossover point seems to be around 5k rows. To get a fast predict
time on fewer than 5k rows, set n_jobs to 1 after fit and before
predict. Alternatives would be to split n_jobs into two parameters,
for fit and predict, or to have a complicated heuristic based on
n_estimators, n_samples, n_features, tree depth, etc.
DOC: Emphasize that n_jobs is for fit and predict methods in random forests.
Merge pull request #1700 from erg/rf

Speed regression in random forests for predicting > 5k rows + clarify docs for n_jobs