Invention Grant
- Patent Title: Automatic selection of high quality training data using an adaptive oracle-trained learning framework
-
Application No.: US14578200Application Date: 2014-12-19
-
Publication No.: US10657457B1Publication Date: 2020-05-19
- Inventor: Shawn Ryan Jeffery , Nick Pendar , Mark Thomas Daly , Matthew DeLand , David Alan Johnston
- Applicant: GROUPON, INC.
- Applicant Address: US IL Chicago
- Assignee: GROUPON, INC.
- Current Assignee: GROUPON, INC.
- Current Assignee Address: US IL Chicago
- Agency: Alston & Bird, LLP
- Main IPC: G06N20/00
- IPC: G06N20/00

Abstract:
In general, embodiments of the present invention provide systems, methods and computer readable media for an adaptive oracle-trained learning framework for automatically building and maintaining models that are developed using machine learning algorithms. In embodiments, the framework leverages at least one oracle (e.g., a crowd) for automatic generation of high-quality training data to use in deriving a model. Once a model is trained, the framework monitors the performance of the model and, in embodiments, leverages active learning and the oracle to generate feedback about the changing data for modifying training data sets while maintaining data quality to enable incremental adaptation of the model.
Information query