Nominal feature transformation using likelihood of outcome
US9619757B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jun 20, 2014 |
| Grant date | Apr 11, 2017 |
| Priority date | — |
| Expiry date | Jun 19, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention relate to transforming a nominal feature to a numeric feature that indicates a likelihood or probability of a particular outcome. Numeric features are determined that indicate a likelihood of an outcome given the value of the collected data (nominal values). Such numeric features are used to represent the corresponding nominal features for use in generating a machine learned model. As such, a nominal feature initially captured in a data set is transformed or converted to a numeric feature that represents a likelihood of a corresponding outcome as opposed to a Boolean value. Upon transforming nominal values to numeric values based on the likelihood of outcome, the numeric values can be used to generate a machine learned model that is used to predict future outcomes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.