Approximate K-means via cluster closures
US9710493B2 · kind B2 · utility
41Cited by
13References
19Claims
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Key dates
| Filing date | Mar 8, 2013 |
| Grant date | Jul 18, 2017 |
| Priority date | — |
| Expiry date | Jun 21, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/35
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A set of data points is divided into a plurality of subsets of data points. A set of cluster closures is generated based at least in part on the subset of data points. Each cluster closure envelopes a corresponding cluster of a set of clusters and is comprised of data points of the enveloped cluster and data points neighboring the enveloped cluster. A k-Means approximator iteratively assigns data points to a cluster of the set of clusters and updates a set of cluster centroids corresponding to the set of clusters. The k-Means approximator assigns data points based at least in part on the set of cluster closures.
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