Multiple output relaxation machine learning model
US8352389B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 20, 2012 |
| Grant date | Jan 8, 2013 |
| Priority date | — |
| Expiry date | Aug 20, 2032 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A multiple output relaxation (MOR) machine learning model. In one example embodiment, a method for employing an MOR machine learning model to predict multiple interdependent output components of a multiple output dependency (MOD) output decision may include training a classifier for each of multiple interdependent output components of an MOD output decision to predict the component based on an input and based on all of the other components. The method may also include initializing each possible value for each of the components to a predetermined output value. The method may further include running relaxation iterations on each of the classifiers to update the output value of each possible value for each of the components until a relaxation state reaches an equilibrium or a maximum number of relaxation iterations is reached. The method may also include retrieving an optimal component from each of the classifiers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.