I want to compare both k means and k harmonic means algorithm in terms of cluster quality. Can anyone suggest a good measure for comparison. Thanks in advance.
Most cluster metrics will be some form of inter. vs intra. cluster distances. The gist of these metrics is to see how how close are members within a cluster and how different are members among clusters. There really isn't a single good metric.
It depends on the input data and what you are looking for in clustering. The best way to compare cluster algorithms is to use real data for benchmarking.
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
version 2.3.6
In my project I am trying to combine both k harmonic mean and Artificial bee colony algorithm.k harmonic mean is used for calculating the fitness value of Artificial bee colony algorithm. And I hope it will improve the quality of clustering. Can you say I am on the right track? please help me if you are working in this area.