1. A computer-implemented method for confirming or rejecting a most relevant example, the method comprising: generating a binary decision model by training a binary classifier using a plurality of training documents; classifying one or more test documents into one of a plurality of document type categories using the binary decision model, wherein the one or more test documents lack a user-defined category label; selecting a most relevant example of the classified test documents from among the classified test documents, wherein the most relevant example of the classified test documents is the test document having a classification score closest to a boundary between a positive decision and a negative decision concerning the test document belonging to a particular one of the plurality of categories; displaying, using a display of the computer, the most relevant example of the classified test documents to a user; receiving, via the computer and from the user, a confirmation or a negation of a classification label of the most relevant example of the classified test documents; and storing the confirmation or the negation of the classification label of the most relevant example of the classified test documents to a memory of the computer.