The previous chapter showed you how to build recommender systems. There are a few options, and some of them can be developed using the recommenderlab package. In addition, each technique has some parameters. After we build the models, how can we decide which one to use? How can we determine its parameters? We can first test the performance of some models and/or parameter configurations and then choose the one that performs best.

This chapter will show you how to evaluate recommender models, compare their performances, and choose the most appropriate model. In this chapter, we will cover the following topics: