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Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming

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R JOURNAL
卷 3, 期 2, 页码 29-33

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R FOUNDATION STATISTICAL COMPUTING
DOI: 10.32614/rj-2011-015

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  1. U.S. National Science Foundation [HRD-0420407]

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The heuristic k-means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp. We demonstrate its advantage in optimality and runtime over the standard iterative k-means algorithm.

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