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When should you use classification over regression?

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Both classification and regression are associated with prediction. Classification involves the identification of values or entities that lie in a specific group. The regression method, on the other hand, entails predicting a response value from a consecutive set of outcomes.

The classification method 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, we have some names of bikes and cars. We would not be interested in finding how these names are correlated to bikes and cars. Rather, we would check whether each name belongs to the bike category or to the car category.