Machine learning with incomplete data sets
US9349105B2 · kind B2 · utility
23Cited by
9References
19Claims
0Family size
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Key dates
| Filing date | Dec 18, 2013 |
| Grant date | May 24, 2016 |
| Priority date | — |
| Expiry date | Aug 15, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine learning solutions compensate for data missing from input (training) data and thereby arrive at a predictive model that is based upon, and consistent with, the training data. The predictive model can be generated within a learning algorithm framework by transforming the training data to generate modality or similarity kernels. Similarity values can be generated for these missing similarity values.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.