Natural Language Processing: Python and NLTK

Classifying with multiple binary classifiers

So far we have focused on binary classifiers, which classify with one of two possible labels. The same techniques for training a binary classifier can also be used to create a multi-class classifier, which is a classifier that can classify with one of the many possible labels. But there are also cases where you need to be able to classify with multiple labels. A classifier that can return more than one label is a multi-label classifier.

A common technique for creating a multi-label classifier is to combine many binary classifiers, one for each label. You train each binary classifier so that it either returns a known label or returns something else to signal that the label does not apply. Then, you ...