Getting Started with Natural Language Processing

6 Linguistic feature engineering for author profiling

This chapter covers

• Improving the implementation of your user profiling algorithm
• Discovering strategies for linguistic feature engineering
• Exploring other useful NLP techniques with NLTK and spaCy
• Applying a Decision Tree classifier with sklearn
• Evaluating a machine-learning classifier in application to an NLP task

The last chapter introduced the task of author (user) profiling and focused on authorship identification. We said that it is a good example of how machine learning can be applied to build an NLP application. This works because

• We can clearly define classes for this task. In particular, you were detecting which of the two authors, Jane Austen (class1) or William Shakespeare ...