Review of the Robust K-means Algorithm and Comparison with Other Clustering Methods
نویسنده
چکیده
In this paper, I will test the Robust K-means algorithm, as developed and implemented by S. Still and L. Bottou, on randomly generated data sets taken from Gaussian distributions. I will then compare the results with the Soft K-means algorithm with Deterministic Annealing and the standard K-means algorithm, using several heuristics for initial centroid placement. I will perform experiments in both 2 dimensional and 20 dimensional space, and compare how the algorithms performance degrades as the problem complexity increases.
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تاریخ انتشار 2008