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Inference-Time Prior Adaptation for Imbalanced Data Streams under Concept Drift
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data streamsconcept driftclass imbalancek-nearest neighbors
2610.33126
Builder Relevance
1h ago80%
Abstract
The paper presents PAI-KNN, a k-nearest neighbor classifier that adapts to concept drift and class imbalance through inference-time prior adjustment instead of memory modification.
Reality Card
Core Claim
PAI-KNN achieves competitive performance in data stream classification under dynamic class imbalance and concept drift without relying on memory modification.
Method / Result
PAI-KNN performs particularly well in scenarios involving dynamic class imbalance and concept drift, evaluated on multiple synthetic data streams.
Limitations
The paper does not specify authors or detailed experimental setups, which may hinder reproducibility.
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