1. A method for improving predictions of a given predictive model using aggregate information, comprising: identifying a plurality of targets to predict in a given domain; receiving raw data set for predicting a plurality of values associated respectively with the plurality of targets in the given domain and predicting the plurality of values; receiving aggregate information associated with the plurality of targets, the aggregate information including estimated or actual values at a coarser level of the plurality of targets; and improving, by a processor, the predicted values of the plurality of targets based on the aggregate information, wherein the improving comprises: summing the plurality of values to determine an aggregated value; subtracting the aggregated value from the aggregate information to determining a corresponding difference; dividing the corresponding difference by a count of the plurality of targets to determine a factor; and adding the factor to each of the plurality of values, wherein the plurality of values with the added factor represents the improved predicted values of the plurality of targets.