Characterizing datasets using sampling, weighting, and approximation of an eigendecomposition
US8412651B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 3, 2010 |
| Grant date | Apr 2, 2013 |
| Priority date | — |
| Expiry date | Jul 28, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, a system, and a computer-readable medium are provided for characterizing a dataset. A representative dataset is defined from a dataset by a computing device. The representative dataset includes a first plurality of data points and the dataset includes a second plurality of data points. The number of the first plurality of data points is less than the number of the second plurality of data points. The data point is added to the representative dataset if a minimum distance between the data point and each data point of the representative dataset is greater than a sampling parameter. The data point is added to a refinement dataset if the minimum distance between the data point and each data point of the representative dataset is less than the sampling parameter and greater than half the sampling parameter. A weighting matrix is defined by the computing device that includes a weight value calculated for each of the first plurality of data points based on a determined number of the second plurality of data points associated with a respective data point of the first plurality of data points. The weight value for a closest data point of the representative dataset is updated if th…
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