Automated quality check and diagnosis for production model refresh
US11605025B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | May 14, 2020 |
| Grant date | Mar 14, 2023 |
| Priority date | — |
| Expiry date | Jan 29, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F17/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
As a data science project goes into the production stage, model maintenance to maintain model quality and predictive accuracy becomes a concern. Manual model maintenance by data scientists can become a time- and labor-intensive process, especially for large scale data science projects. An early warning system addresses this by performing systematic statistical and algorithmic checks for prediction accuracy, stability, and model assumption validity. A diagnostic report is generated that helps data scientists to assess the health of the model and identify sources of error as needed. Well-performing models can be automatically deployed without further human intervention while poor performing models trigger a warning or alert to the data scientists for further investigation and may be removed from production until the performance issues are addressed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.