Optimized training of linear machine learning models
US10318882B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 11, 2014 |
| Grant date | Jun 11, 2019 |
| Priority date | — |
| Expiry date | Oct 27, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An indication of a data source to be used to train a linear prediction model is obtained. The model is to generate predictions using respective parameters assigned to a plurality of features derived from observation records of the data source. The parameter values are stored in a parameter vector. During a particular learning iteration of the training phase of the model, one or more features for which parameters are to be added to the parameter vector are identified. In response to a triggering condition, parameters for one or more features are removed from the parameter vector based on an analysis of relative contributions of the features represented in the parameter vector to the model's predictions. After the parameters are removed, at least one parameter is added to the parameter vector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.