Times series model explainability
US12306909B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 9, 2021 |
| Grant date | May 20, 2025 |
| Priority date | — |
| Expiry date | Mar 21, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for a time series forecaster including a machine learning (ML) model and a time series forecasting algorithm may be used to generate a future forecast model for a time series dataset. The future forecast model includes a future prediction showing a future forecast of the time series dataset. Rather than simply presenting the importance of a forecasting model feature in a limited manner, such as in the form of a number (e.g., a float number), the future forecast model of one or more embodiments may advantageously include at least one forecasting model feature visualization output that visually illustrates the effects of one or more forecasting model features on the future prediction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.