We consider various similarity measures between different clusterings of a dataset, parametrized by the number of clusters. Parallelizing our code, we graph the similiarity between 20 implementations of kmeans for 1 up to 15 clusters. Studying these histograms, we can make a better choice about how many clusters best segregates out linguisitic dataset.
lishali/Stability_of_Kmeans
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How stable are the kmeans clusters in the classifying_linguistic_geograph repo?
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