Selection of most effective machine learning kernel from a training set of documents
US8965814B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 15, 2012 |
| Grant date | Feb 24, 2015 |
| Priority date | — |
| Expiry date | Mar 22, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A server computing system selects a machine learning kernel from a plurality of machine learning kernels using a plurality of training documents. The server computing system identifies a plurality of testing documents from a plurality of electronic discovery documents based on the plurality of training documents. For each of the plurality of machine learning kernels and for each testing document in the plurality of testing documents, the server computing system determines a class of the testing document using a default value for each of a plurality of parameters for the machine learning kernel and evaluates a goodness of fit of the machine learning kernel for the testing document. The server computing system selects a machine learning kernel from the plurality of machine learning kernels and determines a value for at least one of the plurality of parameters for the selected machine learning kernel using a goodness of fit test.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.