When developing machine learning models, you generally benchmark multiple models during the build phase. Then you estimate the performances of those models and select the model which you consider most likely to perform well. You need objective measures of performance to decide which forecast to retain as your actual forecast.
In this chapter, you’ll discover numerous tools for model evaluation. You are going to see different strategies for evaluating machine learning models in general and specific ...
