An efficient implementation of the k-means++ algorithm for clustering multivariate data. It has been shown that this algorithm has an upper bound for the expected value of the total intra-cluster distance which is log(k) competitive. Additionally, k-means++ usually converges in far fewer than vanilla k-means.
Laurent S (2022). k-means++ (https://www.mathworks.com/matlabcentral/fileexchange/28804-k-means), MATLAB Central File Exchange. Retrieved .
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