# Why is handwriting recognition treated as classification problem instead of a regression problem?

I have just started learning about machine learning, and I started reading about handwriting recognition. Apparently (please correct me if I am utterly wrong), handwriting is treated as a classification problem. It makes sense because you are assigning a certain value depending on other factors (e.g. two vertical lines + one horizontal line = "H"). Now, if we were to treat it as a regression problem, would it not work just as fine? It would try to predict the value of the letter by looking at the patterns - just like classification.

Please, correct me if I am wrong. I am just really confused right now.

• This may seem a bit rude, but could you include in your question what the words "classification" and "regression" mean to you? – Matthew Drury Aug 25 '17 at 20:15
• @Aksakal I know what it means : ) I just want us to know the OP's understanding, so we can better help out. – Matthew Drury Aug 25 '17 at 20:29
• Imagine yourself trying to work out what handwriting you're having trouble reading says (like a hastily scrawled name and address, say) ... answering a question like "Is that an '$a$' or a '$c$' or an '$o$'?" is classification. – Glen_b Aug 26 '17 at 0:54
• @Glen_b Thanks for that concise explanation! I was a little bit confused about the terms. – Armando H. Aug 30 '17 at 17:39
• @MatthewDrury I had understood that classification was used to get a value of either 1 or 0 (is it a tumor or is it not?), but I did not know that more terms could be used when I asked the question (What type of tumor?). As I understand, regression is used to predict future values of certain elements based on the values given in a data set. – Armando H. Aug 30 '17 at 17:43