CMune is an enhanced version of Modified Sharp.
Specifically, the number of parameters has been
reduced from three to only two parameters to reduce
the effort needed to select the best parameters. Also
new validation indices; as well as new data sets; have
been adopted for the purpose of comparing the proposed
algorithm with the previous techniques. CMune
Clustering Algorithm is presented for the purpose of
finding clusters of arbitrary shapes and arbitrary
densities in high dimensional feature spaces. It can
find clusters of varying shapes, sizes and densities;
even in the presence of noise and outliers and in high
dimensional spaces as well. It is based on the idea of
letting each data point vote for its K-nearest
neighbors and adopting the points with the highest
votes as clusters' seed

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