Fitting a Simplicial Complex using a Variation of k-means
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We give a simple and effective two stage algorithm for approximating a point cloud S⊂R^m by a simplicial complex K. The first stage is an iterative fitting procedure that generalizes k-means clustering, while the second stage involves deleting redundant simplices. A form of dimension reduction of S is obtained as a consequence.
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