Chapter 6. Evaluating models
This chapter covers
- Calculating model metrics
- Training versus testing data
- Recording model metrics as messages
We’re over halfway done with our exploration of the phases of a machine learning system (figure 6.1). In this chapter, we’ll consider how to evaluate models. In the context of a machine learning system, to evaluate a model means to consider its performance before making it available for use in predictions. In this chapter, we’re going to ask a lot of questions about models.
Figure 6.1. Phases of machine learning
Much of the work of evaluating models may not sound that necessary. If you’re in a hurry ...
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