1. A method of training an initially trained classifier (ITC), the ITC having been generated using a set of verified documents associated with a set of class labels, the set of verified documents having been divided into a training set of documents and a test set of documents, and each class of the set of class labels associated with a class list, the training set of documents having been further divided into an integer number of verified document sets (INVDS), the method comprising: automatically inputting a set of unverified documents into the ITC, the set of unverified documents divided into an integer number of unverified document sets (UNVDS); automatically identifying a subset of documents from the UNVDS; automatically generating a final set of training documents based on the subset of documents and the INVDS; clustering at least one subset of documents from the INVDS and one subset of documents from the UNVDS using a flat clustering or hierarchical clustering technique; and training the ITC using the final set of training documents.