Training method and system for decision tree model, storage medium, and prediction method
US12393884B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 29, 2021 |
| Grant date | Aug 19, 2025 |
| Priority date | — |
| Expiry date | Jun 22, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This application discloses a method to train a decision tree model. The method is performed by a training system. The training system includes N processing subnodes and a main processing node, N being a positive integer greater than 1. The method includes separately obtaining, by each processing subnode for a currently being trained tree node, a node training feature set and gradient data of the currently being trained tree node; separately determining, by each of the processing subnode, a local splitting rule for the currently being trained tree node according to the node training feature set and the gradient data that are obtained, and transmitting the local splitting rule to the main processing node; and selecting, by the main processing node, a splitting rule corresponding to the currently being trained tree node from the local splitting rule determined by each of the processing subnode.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.