Method for using a feed forward neural network to perform classification with highly biased data
US5359699A · kind A · utility
36Cited by
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10Claims
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Key dates
| Filing date | Dec 2, 1991 |
| Grant date | Oct 25, 1994 |
| Priority date | — |
| Expiry date | Dec 2, 2011 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An artificial neural network detects points in feature space outside of a boundary determined by a set of sample data. The network is trained using pseudo data which compensates for the lack of original data representing "abnormal" or novel combinations of features. The training process is done iteratively using a net bias parameter to close the boundary around the sample data. When the neural net stabilizes, the training process is complete. Pseudo data is chosen using several disclosed methods.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.