Binary Drift Detector: McDiarmid Drift Detection Method #1703
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- hence no need to explicit pop left
- instead of handling this internally, needs to be mentioned in doc
aditya0by0
commented
Aug 14, 2025
| if self.drift_detected: | ||
| self._reset() | ||
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| self._sliding_window.append(0 if x == 1 else 1) |
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I'm still confused about the input values for correct prediction and incorrect prediction as mentioned in #1532. Can someone please help me out with this ?
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Hi @aditya0by0. Multiple classic drift detectors seem to use a binary loss scheme, but there might be other patterns nowadays. I am not aware of the specifics of the algorithms you are contributing.
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ok I will check further on it. Btw the following is the corresponding moa code for the algorithm from the author : https://github.com/alipsgh/codes-for-moa/blob/master/drift_detection/MDDM_A.java
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PR for Discussion : #1672
Add McDiarmid Drift Detection Methods (MDDM)
Summary
Implements three new binary drift detectors based on McDiarmid's inequality:
MDDM_A– Arithmetic weighting (linear).MDDM_E– Exponential weighting.MDDM_G– Geometric weighting.