Chapter 1. Simple Classifiers

In this chapter, we will cover the following recipes:

• Deserializing and running a classifier
• Getting confidence estimates from a classifier
• Getting data from the Twitter API
• Applying a classifier to a .csv file
• Evaluation of classifiers – the confusion matrix
• Training your own language model classifier
• How to train and evaluate with cross validation
• Viewing error categories – false positives
• Understanding precision and recall
• How to serialize a LingPipe object – classifier example
• Eliminate near duplicates with the Jaccard distance
• How to classify sentiment – simple version