Logistic regression
The first classification model that we are going to explore is called logistic regression. As you can tell from the name, this method is based on a regression, which we discussed in more detail in the previous chapter. However, this particular regression uses a function that is particularly well suited to classification problems.
This is also a simple and interpretable model, which makes it a great first choice when solving classification problems. There are a variety of existing Go packages that implement logistic regression for you, including github.com/xlvector/hector, github.com/cdipaolo/goml, and github.com/sjwhitworth/golearn. However, in our example, we will implement logistic regression from scratch, so that you can both form a full understanding of what goes into training a model and understand the simplicity of logistic regression. Further, in some cases, you may want to utilize a from-scratch implementation as illustrated in the following section to avoid extra...
