An efficient clustering algorithm from the measure of local Gaussian distribution
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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 ∼O(T× N ×(N)) where T is the iteration steps and N is the number of features.
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