Characterization of amount of training for an input to a machine-learned network
US11630995B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 19, 2018 |
| Grant date | Apr 18, 2023 |
| Priority date | — |
| Expiry date | Feb 17, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The user is to be informed of the reliability of the machine-learned model based on the current input relative to the training data used to train the model or the model itself. In a medical situation, the data for a current patient is compared to the training data used to train a prediction model and/or to a decision function of the prediction model. The comparison indicates the training content relative to the current patient, so provides a user with information on the reliability of the prediction for the current situation. The indication deals with the variation of the data of the current patient from the training data or relative to the prediction model, allowing the user to see how well trained the predication model is relative to the current patient. This indication is in addition to any global confidence output through application of the prediction model to the data of the current patient.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.