One disadvantage of using k-prototypes clustering is that it's not widely implemented, as is the case with k-means clustering routines. Another disadvantage of k-prototypes clustering is that it's ...

The major weakness of k-means clustering is that it only works well with numeric data because a distance metric must be computed. There are a few advanced clustering techniques that can deal with ...