Machine learning concepts
Before we move on to the project itself, let’s just build a background about machine learning concepts. This content is not the main scope of this book; therefore, we will quickly go over a couple of definitions to put us on the same page for the remainder of this book.
A model is a representation of a theory (HAIR Jr. et al, 2019) but is also defined as a simplification or approximation of reality (Burnham & Anderson, 2002). In other words, modeling data involves finding patterns that can help us explain a response, which is the most probable outcome from that observation.
With that said, the model will just reflect the data that it received. For that reason, it is crucial that the input data is clean and representative of the reality we are trying to model. To exemplify this, think about when we see a dataset with too many missing values that are going to be either removed or inputted. Both approaches will certainly have an impact on the...
