Systems and methods for determining relative importance of one or more variables in a non-parametric machine learning model
US10832147B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2019 |
| Grant date | Nov 10, 2020 |
| Priority date | — |
| Expiry date | Dec 17, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for determining relative importance of one or more variables in a non-parametric model include: receiving, raw values of the variables corresponding to one or more entities; processing the raw values using a statistical model to obtain probability values for the variables and an overall prediction value for each entity; determining a plurality of cumulative distributions for the variables based on the raw values and the number of entities having a specific raw value; grouping the variables into a plurality of equally sized buckets based on the cumulative distributions; determining a mean probability value for each bucket; assigning a rank number for each bucket based on the mean probability values; compiling a table for the entities based on the raw values and the buckets corresponding to the raw values; and determining the relative importance of the variables for the entities based on the rank numbers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.