Over the course of this chapter, we have deep-dived into classification models. We have also created and trained our first binary classification application, using FastTree and ML.NET, to predict how good a car's price is. We also created our first multi-class classification application using an SDCA trainer to categorize emails. Lastly, we also dove into how to evaluate a classification model and the various properties that ML.NET exposes to achieve a proper evaluation of your classification models.
In the next chapter, we will deep dive into clustering algorithms with ML.NET and creating a file-type classifier.
