Systems and methods for training predictive models that ignore missing features
US11966850B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 9, 2023 |
| Grant date | Apr 23, 2024 |
| Priority date | — |
| Expiry date | Jun 9, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for training and utilizing predictive models that ignore missing features in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating representations of inputs with missing values. The method includes steps for, at a single layer in a multi-layer model, receiving an input includes a set of one or more values for several features and identifying a missingness pattern of the input, wherein the missingness pattern indicates whether the set of values is missing a value for each of the several features. The method further includes determining a set of one or more transformation weights based on the missingness pattern and transforming the input based on the determined transformation weights.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.