1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure.
1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure. 6. The method of claim 1 , further comprising: identifying one or more exemplar documents used by the predictive coding system to classify a prediction document in the updated set of updated training documents; and identifying a region of the prediction document used by the predictive coding system to determine the classification for the prediction document in the updated set of training documents.