Question - When should Classification be used over Regression?
Answer -
Both classification and regression are associated with prediction. Classification involves the identification of values or entities that lie in a specific group. Regression entails predicting a response value from consecutive sets of outcomes.
Classification is chosen over regression when the output of the model needs to yield the belongingness of data points in a dataset to a particular category.
For example, If you want to predict the price of a house, you should use regression since it is a numerical variable. However, if you are trying to predict whether a house situated in a particular area is going to be high-, medium-, or low-priced, then a classification model should be used.