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 ...

The generalized k means method is based on the minimization of the discrepancy between a random variable (or a sample of this random variable) and a set with k points measured through a penalty ...