There is a set of numerical and categorical independent variables and one dependent variable that is categorical. Some of the categories are far to be related with the rest, but most of them are very related between them, and the difference between one category and another is based on small nuances.

Then, there is some way to measure how related are the categories, among them, in the dependent variable??

  • $\begingroup$ What kind of correlation? Pearson / Spearman are defined only for continuous variables. $\endgroup$ – user2974951 Aug 30 '19 at 11:31
  • $\begingroup$ That's my question $\endgroup$ – juanmah Aug 30 '19 at 11:35
  • $\begingroup$ There is no real correlation measure between nominal values. $\endgroup$ – user2974951 Sep 3 '19 at 5:57
  • $\begingroup$ I disagree, think that the categorical dependent variable is a color. It could be Red, Green, Brown, Yellow and Aquamarine, Turquoise Blue, Sky Blue, Pacific Blue, Cerulean, Navy Blue, Denim, Indigo... The blue nuances are more related between them than the other colors (this is real). And if a yellowish color is predicted as Cerulean is worst than a Turquoisish color is predicted as a Aquamarine (my eyes can not notice the difference). There is a way to 'measure' the wrongness of the prediction error? $\endgroup$ – juanmah Sep 3 '19 at 6:27
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    $\begingroup$ Have a look at stats.stackexchange.com/questions/108007/… $\endgroup$ – user2974951 Sep 3 '19 at 6:48

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