I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. However, I couldn't understand how the Gower distance calculates the difference between binary variables. It seems to me that it is not different from Euclidean distance.
How about binary attributes that have the values "m" and "f", for "male" and "female"?
You do realize that for a dicotomous variable all you can get out is "same" or "different"? The key point difference between distances is not if the value is 1 or 0; but how multiple variables are combined.