In previous chapters, we studied linear regression models in detail. In particular, we found that in all the models described, the response variable takes quantitative values. Often in everyday life, response variables are qualitative instead. For example, we want to determine whether a device is on or off, depending on the noise detected in the environment. Or we want to know whether to issue a credit based on financial information and other personal information. Or we want to diagnose a patient's disease first to select the immediate treatment pending final results.
In each of these cases, we want to explain the probability of having an attribute, or an event occurring, in relation to the number of possible variations of multiple explanatory variables. In other words, we are trying to classify...