The Logistic Regression Algorithm deals in discrete values whereas the Linear Regression Algorithm handles predictions in continuous values. This means that Logistic Regression is a better option for binary classification. An event in Logistic Regression is classified as 1 if it occurs and it is classified as 0 otherwise.
Logistic regression is a supervised learning classification algorithm used to predict the probability of a target variable. The nature of target or dependent variable is dichotomous, which means there would be only two possible classes.
Predicting Customer Response to Telemarketing Campaigns for Term Deposit
Output variable - y - Whether the client has subscribed a term deposit or not
Binomial ("yes" or "no")