Classification vs Regression

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 am not quite sure what the differences are between classification and regression.

From what I understand is that classification is something that is categorical. It's either this or it's either that.

Regression is more of a prediction.

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Both of the problems above would be more of a Regression problem right? It is both using a learning algorithm to predict. Could anyone give an example of Classification vs Regression?

Mar 5 in Machine Learning by Dev
• 6,000 points
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1 answer to this question.

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You are correct: categorization applies a label (or 'class') to any given data point. As you mentioned, this term is category. Consider malware classification: given a file, is it malware or not? (The "label" will be the 'yes' or 'no' answer to this question.)

The purpose of regression, on the other hand, is to forecast an actual value (i.e. not categorical). Predicting someone's weight based on their height and age is an example.

So, in either of the questions you've posed, the answer boils down to what you're looking for from your prediction: a category or a true value?

Regression is the process of finding the relationship and the effect of this relationship on the outcome of the future value of an object, whereas classification is the process of grouping data into categories for the most effective and efficient usage. 2.In order to predict numerical and categorical data, classification is employed, whereas regression is used to forecast numerical data.
answered Mar 9 by Nandini
• 5,480 points

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