-reduction of the total number of sampling points; the sampling rate gradually slows down with the improvement of regression performance, and thus the non-improvement trend will be spotted at an earlier stage; -reduction in average time spent on generating an individual datapoint; a classifier is trained to screen out unpromising data inputs, and thus avoid spending time on unnecessary simulations or experiments.