Analytic system for gradient boosting tree compression
US10956835B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 11, 2019 |
| Grant date | Mar 23, 2021 |
| Priority date | — |
| Expiry date | Mar 11, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing device compresses a gradient boosting tree predictive model. A gradient boosting tree predictive model is trained using a plurality of observation vectors. Each observation vector includes an explanatory variable value of an explanatory variable and a response variable value for a response variable. The gradient boosting tree predictive type model is trained to predict the response variable value of each observation vector based on a respective explanatory variable value of each observation vector. The trained gradient boosting tree predictive model is compressed using a compression model with a predefined penalty constant value and with a predefined array of coefficients to reduce a number of trees of the trained gradient boosting tree predictive model. The compression model minimizes a sparsity norm loss function. The compressed, trained gradient boosting tree predictive model is output for predicting a new response variable value from a new observation vector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.