EFR-IC: Ensemble Fuzzy association Rule-based classifier for Imbalanced data streams with Concept drift
Saeideh Roshanfekr,
Mohammad Reza Razzazi
Abstract:One of the most contestable problems in online learning is concept drift. In addition, if the data stream has imbalanced data, the detection of concept drift is more difficult, especially, when drift is in minority samples. Ensemble classifiers are also effective for the data stream classification with concept drift. By adjusting the weight to every individual classifier, we can manage the concept drift and misclassification problems. Using association rule mining techniques can help in balancing datasets and … Show more
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