1. A method for determining important locations of a classifier, said method comprising: calculating a mean deviation and a standard deviation of every pixel location in a classifier with respect to positive and negative samples associated with said classifier; ranking an importance of all pixel locations calculated with respect to said classifier based on a combination of t-scores and mean differences; and selecting a number of said locations to achieve a detection rate for said classifier for a particular application in order to determine which locations of said classifier are involved in discrimination between class objects and non-class objects.