Although the name Logistic Regression suggests a regression operation, the goal of Logistic Regression is classification. In a very rigorous world such as statistics, why is this technique ambiguously named? Simple, the name is not wrong at all, and it makes perfect sense: it just requires a bit of an introduction and investigation. After that you'll fully understand why it's named Logistic Regression, and you'll no longer think that it's a wrong name.
First, let's introduce what a classification problem is, what a classifier is, how it operates, and what its output is.
In the previous chapter, we presented regression as the operation of estimating a continuous value in a target variable; mathematically speaking, the predicted variable is a real number in the range (−∞, +∞). Classification, instead, predicts a class, that is, an index in a finite set of classes. The simplest case is named binary classification, and the output is typically a Boolean value ...
