Parallel processing machine learning decision tree training
US9171264B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 15, 2010 |
| Grant date | Oct 27, 2015 |
| Priority date | — |
| Expiry date | Nov 27, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/955
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments are disclosed herein that relate to generating a decision tree through graphical processing unit (GPU) based machine learning. For example, one embodiment provides a method including, for each level of the decision tree: performing, at each GPU of the parallel processing pipeline, a feature test for a feature in a feature set on every example in an example set. The method further includes accumulating results of the feature tests in local memory blocks. The method further includes writing the accumulated results from each local memory block to global memory to generate a histogram of features for every node in the level, and for each node in the level, assigning a feature having a lowest entropy in accordance with the histograms to the node.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.