When it comes to identifying and classifying email as spam, a process known as spam detection, the task involves analyzing emails to determine whether they should be categorized as spam or not, which is a binary classification problem. In this context, the term "factor variable" refers to a categorical variable that differentiates between two categories: spam and non$-$spam emails. To effectively perform this task, various machine learning methods can be employed, each with its unique approach to modeling and predicting categorical outcomes. Which of the following methods are appropriate for this task?

Options:

A$.$ Multiple linear regression

B$.$ Logistic regression

C$.$ Regression tree