I'm trying to do fuzzy k-means clustering on a dataset using the cmeans function (R) . The problem Im facing is that the sizes of clusters are not as I would like them to be. This is done by calculating the cluster to which the observations are "closest".
cl$size  108 31 192 51 722 18460 67 1584 419 17270
Here we see that for 10 clusters we have two huge clusters and a lot of very small ones. Does this imply that two clusters are optimal in any way? If I do regular K-means 10 segments look very well, with good sizes and their intepretation makes a lot of sense but I would like to try fuzzy correctly. I just started exploring this fuzzy clustering so any help and pointers are overly welcome.