1. A computer-implemented method of classifier set prediction, comprising: dividing, by a computer, a future time interval into a plurality of minimum subintervals; and for a selected minimum subinterval: retrieving, by the computer, data for one or more historic time intervals corresponding to the selected minimum subinterval; and determining, by the computer, a best performing classifier set for the one or more historic time intervals corresponding to the selected minimum subinterval by comparing performing classifier sets for each historic time interval.
1. A computer-implemented method of classifier set prediction, comprising: dividing, by a computer, a future time interval into a plurality of minimum subintervals; and for a selected minimum subinterval: retrieving, by the computer, data for one or more historic time intervals corresponding to the selected minimum subinterval; and determining, by the computer, a best performing classifier set for the one or more historic time intervals corresponding to the selected minimum subinterval by comparing performing classifier sets for each historic time interval. 2. The method of claim 1 , wherein determining the best performing classifier set for the one or more historic time intervals comprises: for each of the one or more historic time intervals, applying a complete set of classifiers to a set of image queries received during the historic time interval; and determining the best performing classifier set for the historic time interval.