Let's say we are classifying Images of cat , fish and human. Classifying a cat as human is as wrong as classifying it as fish, so here the normal loss functions/ metrics like Confusion matrix is fine.

But in the case of classifying a baby, child, teen, man, old-man. Classifying a child as old man is more wrong than classifying as a teen. So what would be a better metric for a ranking kind of classification?

  • $\begingroup$ Why not use categories of Age? Then if your categories are numerical you can simply compare the numbers. $\endgroup$
    – grldsndrs
    Jul 14 '19 at 14:32
  • $\begingroup$ that is just an example, my question what to do for such kind of rank able categorical data. $\endgroup$
    – Pardhu
    Jul 14 '19 at 14:39
  • 1
    $\begingroup$ This kind of problem is known as "ordinal regression" (or the less common but more correct "ordinal classification"). datascience.stackexchange.com/questions/23233/… $\endgroup$ Jul 15 '19 at 0:56

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.