System to identify and explore relevant predictive analytics tasks of clinical value and calibrate predictive model outputs to a prescribed minimum level of predictive accuracy
US11651289B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 5, 2019 |
| Grant date | May 16, 2023 |
| Priority date | — |
| Expiry date | Oct 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of implementing a task complexity learning system, including: learning a model for predicting the value of a continuous task variable y based upon an input variable x; learning an encoder that encodes a continuous task variable y into an encoded task value; calculating a loss function based upon the predicted value of y output by the model and the encoded task value output by the encoder; calculating a distortion function based upon the input continuous task variable y and the encoded task value, wherein learning the model and learning the encoder includes minimizing an objective function based upon the loss function and the distortion function for a set of input training data including x, y pairs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.