[FIXED] Classification vs Regression?

Issue

I 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.

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?

Solution

You are correct: given some data point, classification assigns a label (or 'class') to that point. This label is, as you said, categorical. One example might be, say, malware classification: given some file, is it malware or is it not? (The "label" will be the answer to this question: 'yes' or 'no'.)

But in regression, the goal is instead to predict a real value (i.e. not categorical). An example here might be, given someone's height and age, predict their weight.

So in either of the questions you've quoted, the answer comes down to what you are trying to get out of your prediction: a category, or a real value?

(A side note: there are connections and relations between the two problems, and you could, if you wanted, see regression as an extension of classification in the case where the labels are ordinal and there are infinite labels.)

Answered By - ryan