Automatically adjusting system activities based on trained machine learning model
US12307473B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2022 |
| Grant date | May 20, 2025 |
| Priority date | — |
| Expiry date | Jul 27, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to predict a first predicted assessment score at a first instance and a second predicted assessment score at a second instance with respect to a second user. The computing system determines whether the first predicted assessment score is different from the second predicted assessment score, and whether a first data entry of the personal data set of the second user changed between the first instance and the second instance. The computing system takes or recommends an action corresponding to a reversal in the change in the first data entry in order to alter the predicted assessment score of the second user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.