Chapter 7. Text Classification

In this chapter, we will cover the following recipes:

• Bag of words feature extraction
• Training a Naive Bayes classifier
• Training a decision tree classifier
• Training a maximum entropy classifier
• Training scikit-learn classifiers
• Measuring precision and recall of a classifier
• Calculating high information words
• Combining classifiers with voting
• Classifying with multiple binary classifiers
• Training a classifier with NLTK-Trainer