Determining a number of kernels using imbalanced training data sets
US9798982B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 20, 2015 |
| Grant date | Oct 24, 2017 |
| Priority date | — |
| Expiry date | Oct 1, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Determining a number of kernels within a model is provided. A number of kernels that include data samples of a majority data class of an imbalanced training data set is determined based on a set of generated artificial data samples for a minority data class of the imbalanced training data set. The number of kernels within the model is generated based on the set of generated artificial data samples. A likelihood of the set of generated artificial data samples being included in the majority data class of the imbalanced training data set is calculated. Parameters of each kernel in the number of kernels are updated based on the likelihood of the set of generated artificial data samples being included in the majority data class of the imbalanced training data set. Each kernel in the number of kernels is adjusted based on the updated parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.