Machine learning feature engineering
US11354596B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 18, 2020 |
| Grant date | Jun 7, 2022 |
| Priority date | — |
| Expiry date | May 18, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine learning feature engineering systems and methods comprise an event ingestion module that receives event data associated with entities. The ingestion module determines which entities are associated with events of the event data. The ingestion module stores the events, grouped by associated entity, in a related event store. A user defines features associated with the entities via an API and/or a feature studio. A feature computation layer determines values for the features based on the grouped events stored to the related event store. The feature computation layer stores the computed feature values and timestamps to a feature store. When new data is received, the feature computation layer computes one or more of the feature values for different times based on the timestamps. Feature vectors are generated using the computed feature values and output to the user via the API and/or feature studio.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.