Dynamic Hierarchical Empirical Bayes and digital content control
US10956930B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 12, 2018 |
| Grant date | Mar 23, 2021 |
| Priority date | — |
| Expiry date | Jan 20, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Dynamic Hierarchical Empirical Bayes techniques and systems are described that are implemented to control output of digital content. In one example, a system identifies splitting variables included in data. An amount of loss is then determined for each of the identified splitting variables by the system using a loss function. Based on the determined amounts of loss, the system selects at least one splitting variable from the plurality of splitting variables that are to be used to partition data in a respective node, e.g., a parent node to form a plurality of child nodes. The system, for instance, may select the splitting variable that minimizes the cost, i.e., has the lowest amount of cost. The selected splitting variable is then employed by the system to generate at least one hierarchical level of the hierarchical structure of the statistical model by partitioning data from the parent node into respective child nodes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.