A Better k-means plus plus Algorithm via Local Search
international conference on machine learning(2019)
摘要
In this paper, we develop a new variant of k-means++ seeding that in expectation achieves a constant approximation guarantee. We obtain this result by a simple combination of k-means++ sampling with a local search strategy. We evaluate our algorithm empirically and show that it also improves the quality of the solution in practice.
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