Developing a Pipeline to Benchmark Drift Management Strategies

With guidance from mentors Ray Andrew and Sandeep Madireddy under the LAST project, I aim to develop a pipeline to benchmark the efficacy of various drift management algorithms.

Despite the abundance of literature on this subject, reproducibility remains a challenge due to the lack of available source code. As such, by crafting this pipeline, I aim to create standardized platform for researchers and practitioners to compare several state-of-the-art drift management approaches. Through rigorous testing and benchmarking, we seek to identify the most effective algorithms across a spectrum of drift scenarios, including gradual, sudden, and recurring drift.

This final deliverable of this pipeline will be packaged into a Chameleon Trovi Artifact. The pipeline will also be made easily extensible to cater to additional datasets or any custom-made drift-mitigation methods. This is my proposal for the project.

See you around!