System and method for learning models from scarce and skewed training data
US7630950B2 · kind B2 · utility
6Cited by
8References
20Claims
0Family size
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Key dates
| Filing date | Aug 18, 2006 |
| Grant date | Dec 8, 2009 |
| Priority date | — |
| Expiry date | Jan 21, 2028 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for learning models from scarce and/or skewed training data includes partitioning a data stream into a sequence of time windows. A most likely current class distribution to classify portions of the data stream is determined based on observing training data in a current time window and based on concept drift probability patterns using historical information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.