Concurrent binning of machine learning data
US9672474B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 17, 2014 |
| Grant date | Jun 6, 2017 |
| Priority date | — |
| Expiry date | Oct 16, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Variables of observation records to be used to generate a machine learning model are identified as candidates for quantile binning transformations. In accordance with a particular concurrent binning plan generated for a particular variable, a plurality of quantile binning transformations are applied to the particular variable, including a first transformation with a first bin count and a second transformation with a different bin count. The first and second transformations result in the inclusion of respective parameters or weights for binned features in a parameter vector of the model. In a post-training phase run of the model, at least one parameter corresponding to a binned feature is used to generate a prediction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.