Methods for automatically configuring performance evaluation schemes for machine learning algorithms
US11681931B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 24, 2019 |
| Grant date | Jun 20, 2023 |
| Priority date | — |
| Expiry date | Mar 2, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system that provides a mathematical formulation for new problem of model validation and model selection in presence of test data feedback. The system comprises a memory that stores computer-executable components. A processor, operably coupled to the memory, executes the computer-executable components stored in the memory. A selection component selects a metric of performance evaluation accuracy; and a configuration component configures performance evaluation schemes for machine learning algorithms. A characterization component employs a supervised learning-based approach to characterize relationship between the configuration of the performance evaluation scheme and fidelity of performance estimates; and an optimization component that optimizes accuracy of the machine learning algorithms as a function of size of training data set relative to size of validation data set through selection of values associated with the configuration parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.