This repository presents "EDIST2: Error Distance Approach for Drift Detection and Monitoring" proposed by Imen Khamassi et al.(Self-Adaptive Windowing Approach for Handling Complex Concept Drift).
- JDK 7+
- MOA 2016+
- EDIST2 was proposed in order to deal with these complex drifts EDIST2 monitors the learner performance through a self-adaptive window that is autonomously adjusted through a statistical hypothesis test. This statistical test provides theoretical guarantees, regarding the false alarm rate, which were experimentally confirmed.
- Jorge C. Chamby-Diaz - Initial work - jchambyd
This project is licensed under the MIT License - see the LICENSE.md file for details