Augmenting incomplete training datasets for use in a machine learning system
US11080618B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 7, 2017 |
| Grant date | Aug 3, 2021 |
| Priority date | — |
| Expiry date | Apr 1, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for augmenting incomplete training dataset for use in a machine learning system are described herein. In an embodiment, a server computer receives a plurality of input training datasets including one or more incomplete input training datasets and one or more complete datasets which contain one or more failure training datasets, the incomplete input training datasets comprising a plurality of parameters. Using the one or more failure training datasets, the server computer generates temporal failure data describing a likelihood of failure of an item as a function of time. Using the one or more complete training datasets, the server computer generates parameter specific likelihoods of failure of an item. The server computer augments the one or more incomplete input training datasets using the temporal failure data and/or the parameter specific likelihoods of failure to create one or more augmented training datasets. The server computer uses the one or more augmented training datasets as input for training a machine learning model that is programmed to generate a probability of failure of a particular item represented by an input dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.