Scalable generation of multidimensional features for machine learning
US11295229B1 · kind B1 · utility
3Cited by
3References
18Claims
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Key dates
| Filing date | Apr 19, 2016 |
| Grant date | Apr 5, 2022 |
| Priority date | — |
| Expiry date | Jul 2, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An approximate count of a subset of records of a data set is obtained using one or more transformation functions. The subset comprises records which contain a first value of one input variable, a second value of another input variable, and a particular value of a target variable. Using the approximate count, an approximate correlation metric for a multidimensional feature and the target variable is obtained. Based on the correlation metric, the multidimensional feature is included in a candidate feature set to be used to train a machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.