Automated machine learning using nearest neighbor recommender systems
US11941541B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 10, 2020 |
| Grant date | Mar 26, 2024 |
| Priority date | — |
| Expiry date | Jan 26, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, computer program products and/or systems are provided that perform the following operations: obtaining a performance matrix representing accuracies obtained by executing a plurality of pipelines on a plurality of training data sets, wherein a pipeline comprises a series of operations performed on a data set; selecting a defined number of top pipelines as potential pipelines for a testing data set based, at least in part, on a similarity between the testing data set and each of the plurality of training data sets represented in the performance matrix; storing results from executing each of the potential pipelines as a new data set; determining a pipeline accuracy for each of the potential pipelines when executed against the testing data set; and providing a recommended pipeline for use with the testing data set based, at least in part, on the pipeline accuracy for each potential pipeline.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.