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Article
Online concept evolution detection based on active learning
Concept evolution detection is an important and difficult problem in streaming data mining. When the labeled samples in streaming data insufficient to reflect the training data distribution, it will often furt...
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Article
Global-local information based oversampling for multi-class imbalanced data
Multi-class imbalanced classification is a challenging problem in the field of machine learning. Many methods have been proposed to deal with it, and oversampling is one of the most popular techniques which al...
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Article
Concept drift detection and accelerated convergence of online learning
Streaming data has become an important form in the era of big data, and the concept drift, as one of the most important problem of it, is often studied deeply. However, similar to true concept drift, noise and...
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Article
Granular support vector machine: a review
The time complexity of traditional support vector machine (SVM) is \(O(l^{3})\) ...