Hi When using kmedoids with a mixed distance function, how to interpret the centroids for the nominal variables? Is it some kind of mean distance? Thanks andΒ best regards, Carlos
well the nominal distance between equal values is zero - between differing values it is one. Hence for the nominal variables, the centroid is that point, that is the most equal to the other points - which has the most matches among the nominal variables.
Answers
well the nominal distance between equal values is zero - between differing values it is one. Hence for the nominal variables, the centroid is that point, that is the most equal to the other points - which has the most matches among the nominal variables.
Best regards,
Tobias
But the centroid table is coding the polynomial variables into numbers (which probably represent the indices of the corresponding value).
Is there a way to convert them automatically back to the original (polynomail) values, to make the centroids easier to read?
Carlos
Carlos