Supervised Learning in Game Data Science: Model Validation and Evaluation

Abstract

This chapter focuses on two specific steps in the machine learning process, called model validation and model evaluation. Specifically, model validation is the step used to tune the hyperparameters of the model. Here, we often integrate a cross-validation process, which we discuss in detail in this chapter. Model evaluation, on the other hand, is the process of testing the performance of the model using unseen data, the test dataset. These processes are used to ensure that the model we developed through the algorithms discussed in Chapter 6 are reliable, given our data. The chapter will include labs to give you a practical introduction to these steps, given the modeling techniques discussed in the last chapter.