Privacy preserving ensemble learning as a service
US12169557B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 18, 2021 |
| Grant date | Dec 17, 2024 |
| Priority date | — |
| Expiry date | Dec 20, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques described herein relate to a method for predicting results using ensemble models. The method may include receiving trained model data sets from a model source nodes, each trained model data set comprising a trained model, an important feature list, and a missing feature generator; receiving a prediction request data set; making a determination that the prediction request data set does not include an input feature for a trained model; generating, based on the determination and using a missing feature generator, a substitute feature to replace the input feature; executing the trained model using the prediction request data set and the substitute feature to obtain a first prediction; executing a second trained model using the prediction request data set to obtain a second prediction; and obtaining a final prediction using the first prediction, the second prediction, and an ensemble model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.