1. A computer-implemented method for generating a training set for use during document review, comprising: assigning classification codes to a set of documents; receiving further classification codes assigned to the same set of documents; comparing the classification code for at least one document with the further classification code for that document; determining whether a disagreement exists between the assigned classification code and the further classification code for at least one document; identifying those documents with disagreeing classification codes as training set candidates; applying a stop threshold to the training set candidates, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and designating the training set candidates as a training set when the stop threshold is satisfied.
1. A computer-implemented method for generating a training set for use during document review, comprising: assigning classification codes to a set of documents; receiving further classification codes assigned to the same set of documents; comparing the classification code for at least one document with the further classification code for that document; determining whether a disagreement exists between the assigned classification code and the further classification code for at least one document; identifying those documents with disagreeing classification codes as training set candidates; applying a stop threshold to the training set candidates, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and designating the training set candidates as a training set when the stop threshold is satisfied. 6. A method according to claim 1 , further comprising: associating a confidence score to one or more of the automatically classified documents.