1. A method for training a classifier to classify elements of a data set according to a predetermined characteristic, said data set including N elements, said elements each characterized by at least one feature, said method comprising: forming a first labeled subset of elements from said data set, said elements of said first labeled subset each labeled according to whether said element includes said predetermined characteristic; training an algorithmic classifier to classify for said predetermined characteristic according to said first labeled subset thereby determining which at least one feature is relevant to classifying for said predetermined characteristic; and querying with said classifier an inverted index, said inverted index formed over said at least one feature and generated from said data set, thereby generating a ranked set of elements from said data set, wherein said method further comprises: forming a second labeled subset, said second labeled subset including a predetermined number P of elements labeled according to whether each element includes said characteristic, wherein said P elements in said second labeled subset includes a first subset of K=α×P elements selected randomly from said N elements of said data set, with number α ranging from 0 to 1, and a second subset of M=(1−α)×P elements selected from said ranked set of elements.