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Explain when should you use classification over regression?
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Answer / Aneej Yadav
Classification is used for problems where the output variable is a categorical label, like spam/not spam or win/lose. Regression, on the other hand, is used for problems where the output variable is a continuous value, like predicting a person's age or house price. Classification algorithms like logistic regression, decision trees, random forests, and support vector machines can handle multiple classes, while regression algorithms like linear regression and decision trees regressor are limited to single outputs.
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