In the Matlab version of the K-means algorithm, there is a very useful flag that indicates the action to take if a cluster loses all member observations during the optimization. There are 3 possibilities in Matlab: 1/ treat empty cluster as an error, 2/ remove any clusters that become empty, 3/ Create a new cluster consisting of the one point furthest from its centroid
Does any one know what happens in DAAL K-means in that case? I could not find anything in the documentation about this.
Thanks a lot!