Closed michaelchiucw closed 1 year ago
The first image is MOA-18.06 The second image is MOA-19.05 (latest version) Stream: 100,000 instances 0-50,000: Agrawal f1 balanced class 50,001-100,000: Agrawal f10 balanced class The rest of the setting I didn't mention here are in MOA default.
I have recently tried this with the latest version of MOA (2023.04.0). This issue has been resolved.
Hi there,
I have found an issue about the ADWIN change detector. The ADWIN change detector in the latest MOA release (MOA 19.05.0) will always drops the prequential accuracy to 50% steadily. This issue is regardless the base learner.
You should be able to recreate this issue by simply create a concept drift stream and use the DriftDetectionMethodClassifier with using ADWIN as change detector. You can pick any base learner as you like, say, the most basic one: Naive bayes. For the evaluator, I used FadingFactor with default alpha 0.999. With these settings, you will then see the performance chart will drop to 50% quickly after the drift detection. The performance will then keep at 50% extremely steady.
The ADWIN change detector was fine in version 18.06, as I have been using this version of MOA in my research.