Distributable clustering model training system
US11055620B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 17, 2020 |
| Grant date | Jul 6, 2021 |
| Priority date | — |
| Expiry date | Nov 17, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing system trains a clustering model. (A) Beta distribution parameter values are computed for each cluster using a mass parameter value and a responsibility parameter vector of each observation vector. (B) Parameter values are computed for a normal-Wishart distribution for each observation vector included in a batch of a plurality of observation vectors. (C) Each responsibility parameter vector defined for each observation vector of the batch is updated using the beta distribution parameter values, the parameter values for the normal-Wishart distribution, and a respective observation vector of the selected batch of plurality of observation vectors. (D) A convergence parameter value is computed. (E) (A) to (D) are repeated until the convergence parameter value indicates the responsibility parameter vector defined for each observation vector is converged. A cluster membership is determined for each observation vector using the responsibility parameter vector. The determined cluster membership is output for each observation vector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.