A distance-based point-reassignment heuristic for the k-hyperplane clustering problem

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Summary

This work proposes a heuristic in which many “critical” points are reassigned at each iteration of the k-Hyperplane Clustering problem, which outperforms the best available one proposed by Bradley and Mangasarian on a set of real-world and structured randomly generated instances.

Type
article
Published
2013-05-16
Cited by
6
References
43

Keywords

Hyperplane, Mathematics, Partition (number theory), Combinatorics, Heuristic

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