Changed the behaviour of "boosting_steps_before_pruning_is_done"

Changed the behaviour of "boosting_steps_before_pruning_is_done". Its default value is now 0. When 0, pruning is not done. Positive values work in the same manner as in the previous version. The reason why pruning is not done by default is that pruning can significantly increase training time on larger datasets and when the model gets many terms. Pruning may increase model predictiveness (usually slightly).