Systems and methods for configuring and implementing an interpretive surrogate machine learning model
US10929756B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 21, 2020 |
| Grant date | Feb 23, 2021 |
| Priority date | — |
| Expiry date | Jul 21, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for implementing an interpretive proxy model includes evaluating a deep learning model; estimating a subset of a plurality of distinct algorithmic features of the deep learning model as leading contributors of a subject predictive output of the deep learning model; constructing a proxy model using algorithmic features of the deep learning model within the subset of the plurality of distinct algorithmic features; training the proxy model to mirror predictive outputs of the deep learning model; deploying the proxy model alongside the deep learning model based on a completion of the training; and in response to a same input to both the deep learning model and the proxy model, exposing: (1) a predictive output of the deep learning model, and (2) an explanation of the predictive output of the deep learning model based on leading contributing algorithmic features of the proxy model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.