Learning Data Mining with Python - Second Edition

Authorship attribution

Authorship attribution (as distinct from authorship analysis) is a classification task by which we have a set of candidate authors, a set of documents from each of those authors namely the training set, and a set of documents of unknown authorship otherwise known as the test set. If the documents of unknown authorship definitely belong to one of the candidates, we call this a closed problem, as per the following diagram:

If we cannot be sure of that the actual author is part of the training set, we call this an open problem. This distinction isn't just specific to authorship attribution - any data mining application ...