Logistic regression is famous because it can convert the values of logits (log-odds), which can range from −∞ to +∞ to a range between 0 and 1. As logistic functions output the probability of occurrence of an event, it can be applied to many real-life scenarios. It is for this reason that the logistic regression model is very popular. Another reason why logistic fairs in comparison to linear regression is that it is able to handle the categorical variables.
