Chapter 14. Training a classifier
This chapter covers
- Extracting features from text
- Converting features for Mahout’s use
- Training two Mahout classifiers
- Selecting from among Mahout’s learning algorithms
This chapter explores the first stage in classification: training the model. Developing a classifier is a dynamic process that requires you to think creatively about the best way to describe the features of your data and to consider how they will be used by the learning algorithm you choose to train your models. Some kinds of data lend themselves readily to classification; others offer a greater challenge, which can be rewarding, frustrating, and interesting all at once.
In this chapter, you’ll learn how to choose and extract features ...
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