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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?

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  • $\begingroup$ Why not use categories of Age? Then if your categories are numerical you can simply compare the numbers. $\endgroup$ – grldsndrs Jul 14 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 at 14:39
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    $\begingroup$ This kind of problem is known as "ordinal regression" (or the less common but more correct "ordinal classification"). datascience.stackexchange.com/questions/23233/… $\endgroup$ – Ben Reiniger Jul 15 at 0:56

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