4. A computer implemented method for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the method comprising: providing a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; performing a document classification process on the document collection; automatically generating with a random selection module a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and performing a manual document review process on the random validation set of documents to validate overall results of all of the documents classified by the document classification process; and dynamically and in real-time measuring and displaying on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process.
4. A computer implemented method for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the method comprising: providing a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; performing a document classification process on the document collection; automatically generating with a random selection module a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and performing a manual document review process on the random validation set of documents to validate overall results of all of the documents classified by the document classification process; and dynamically and in real-time measuring and displaying on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process. 5. The method of claim 4 , further comprising allowing a user to monitor the best case estimate of the overall classification quality and terminate the document review process and change parameters and/or instruction for the document classification process based on the best case estimate of the overall classification quality being equal to or lower than the predetermined quality threshold of the documents in the random selected document set.