Method and apparatus for training model based on random forest
US11276013B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 28, 2018 |
| Grant date | Mar 15, 2022 |
| Priority date | — |
| Expiry date | Jul 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F9/5066
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and apparatuses for training model based on random forest are provided. The method includes: dividing worker nodes into one or more groups; performing random sampling, by worker nodes in each group, in the preset sample data to obtain the target sample data; and training, by the worker nodes in each group, one or more decision tree objects using the target sample data. Example embodiments of the present disclosure do not need to scan the complete sample data for once, thereby greatly reducing the amount of data to be read, the time cost, and further the iterative update time of the model. The efficiency of training is improved.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.