EDIST2

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).

Getting Started

Prerequisites

• JDK 7+
• MOA 2016+

Features

• 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.

Authors

• Jorge C. Chamby-Diaz - Initial work - jchambyd

License

This project is licensed under the MIT License - see the LICENSE.md file for details