| 发明名称 |
COMMON FEATURE PROTOCOL FOR COLLABORATIVE MACHINE LEARNING |
| 摘要 |
The disclosed embodiments provide a system for processing data. During operation, the system obtains a hierarchical representation containing a set of namespaces of a set of features shared by a set of statistical models. Next, the system uses the hierarchical representation to obtain, from one or more execution environments, a subset of the features for use in calculating the derived feature. The system then applies a formula from the hierarchical representation to the subset of the features to produce the derived feature. Finally, the system provides the derived feature for use by one or more of the statistical models. |
| 申请公布号 |
US2017109652(A1) |
申请公布日期 |
2017.04.20 |
| 申请号 |
US201615046199 |
申请日期 |
2016.02.17 |
| 申请人 |
LinkedIn Corporation |
发明人 |
Stein David J.;Miao Xu;Wall Lance M.;Young Joel D.;Huang Eric;Gu Songxiang;Teng Da;Tsai Chang-Ming;Rangwala Sumit |
| 分类号 |
G06N99/00;G06F17/30 |
主分类号 |
G06N99/00 |
| 代理机构 |
|
代理人 |
|
| 主权项 |
1. A method, comprising:
obtaining a hierarchical representation comprising a set of namespaces of a set of features shared by a set of statistical models; and calculating, by one or more computer systems, a derived feature from the set of features by:
using the hierarchical representation to obtain, from one or more execution environments, a subset of the features for use in calculating the derived feature; andapplying a formula from the hierarchical representation to the subset of the features to produce the derived feature; and providing the derived feature for use by one or more of the statistical models. |
| 地址 |
Mountain View CA US |
