I created dummy variables (binary data) from categorical variables where I want to partition N subjects into multiple classes by some clustering method. I created a Jaccard similarity index matrix for all subjects, thus having N by N similarity matrix.
My question is, if it is OK to apply a hierarchical clustering using eucledian distance measure on the Jaccard similarity index matrix.
The result looks very good and valid. In fact much better than when I use the jaccard dissimilarity (1-Jaccard index) matrix. I want to make sure that I am not creating mathematical nonsense.