Logistic regression

Logistic regression is another crucial statistical technique, which is primarily used for binary classification problems. Instead of predicting continuous outcomes, logistic regression predicts the probability of an event occurring, typically expressed as a “yes” or “no” outcome. This method is particularly useful for scenarios where we need to model the likelihood of an event, such as whether a customer will churn or not or whether an email is spam or not. Logistic regression models the relationship between the independent variables and the log odds of the binary outcome.

Frameworks

We will explore two approaches to implementing linear and logistic regression in R. First, we will use the base R framework, which is an excellent starting point to understand the underlying concepts and functions. Then, we will dive into tidymodels, a modern and tidy approach to modeling and machine learning in R. tidymodels provides a consistent and...