Chapter 6

Model Evaluation

Learning Objectives

By the end of this chapter, you will be able to:

  • Explain the importance of evaluating models
  • Evaluate regression and classification models using a number of metrics
  • Choose the right metric for evaluating and tuning a model
  • Explain the importance of hold-out datasets and types of sampling
  • Perform hyperparameter tuning to find the best model
  • Calculate feature importance and explain why they are important

This chapter introduces us to how we can improve a model's performance by using hyperparameters and model evaluation metrics.


In the previous three chapters, we discussed the two types of supervised learning problems, regression and classification, followed by ensemble models, ...

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