How to set weight in Weighted Kernel K-Means?
These weights should be introduced by a user. With a weight you tell the K-means algorithm, that one feature is more important than the other.


  [0] These might represent a measure of importance, a frequency count, or some other information. The intent is that a point with a weight of 5.0 is twice as "important" as a point with a weight of 2.5, for instance. This gives rise to the "weighted" K-Means problem. 


[0] http://people.sc.fsu.edu/~jburkardt/m_src/kmeans/kmeans.html