DISCERN: diversity-based selection of centroids for k-estimation and rapid non-stochastic clustering

One of the applications of center-based clustering algorithms such as K-means is partitioning data points into K clusters. In some examples, the feature space relates to the underlying problem we are trying to solve, and sometimes we can obtain a suitable feature space. Nevertheless, while K-means i...

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