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 ...

K-medoids: This is similar to the k-means, but the center is calculated using a median algorithm. Fuzzy : Each point can be a member of multiple clusters that are calculated using any type of ...