System and method for machine learning architecture for enterprise capitalization
US11556992B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 14, 2020 |
| Grant date | Jan 17, 2023 |
| Priority date | — |
| Expiry date | Jul 15, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are described in relation to specific technical improvements adapted for machine learning architectures that conduct classification on numerical and/or unstructured data. In an embodiment, two neural networks are utilized in concert to generate output data sets representative of predicted future states of an entity. A second learning architecture is trained to cluster prior entities based on characteristics converted into the form of features and event occurrence such that a boundary function can be established between the clusters to form a decision boundary between decision regions. These outputs are mapped to a space defined by the boundary function, such that the mapping can be used to determine whether a future state event is likely to occur at a particular time in the future.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.