Methods and apparatuses for building data identification models
US11551036B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 24, 2018 |
| Grant date | Jan 10, 2023 |
| Priority date | — |
| Expiry date | Nov 11, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides methods and an apparatuses for building a data identification model. One exemplary method for building a data identification model includes: performing logistic regression training using training samples to obtain a first model, the training samples comprising positive and negative samples; sampling the training samples proportionally to obtain a first training sample set; identifying the positive samples using the first model, and selecting a second training sample set from positive samples that have identification results after being identified using the first model; and performing Deep Neural Networks (DNN) training using the first training sample set and the second training sample set to obtain a final data identification model. The methods and the apparatuses of the present disclosure improve the stability of data identification models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.