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An efficient clustering algorithm from the measure of local Gaussian distribution (1709.08470v2)
Published 13 Sep 2017 in cs.DB and cs.LG
Abstract: In this paper, I will introduce a fast and novel clustering algorithm based on Gaussian distribution and it can guarantee the separation of each cluster centroid as a given parameter, $d_s$. The worst run time complexity of this algorithm is approximately $\sim$O$(T\times N \times \log(N))$ where $T$ is the iteration steps and $N$ is the number of features.