Bayesian classifier is a process of identifying concepts using a certain representative documents in a particular category. The classifier has the ability to discern other responsive documents in the larger collection and place them in a category. Typically, a category is represented by a collection of words and their frequency of occurrence within the document. The probability that a document belongs to a category is based on the product of each word of the document appearing in that category across all documents. Thus, the learning classifier is able to apply words present in a sample category and apply that knowledge to other new documents. In the e-discovery context, a Bayesian classifier can quickly place documents into confidential, privileged, responsive documents and other well-known categories.