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Learning from imbalanced data poses significant challenges for machine learning algorithms, as they need to deal with uneven distribution of examples in the training set. As standard classifiers will be biased towards the majority class there exist a need for specific methods than can overcome this single-class dominance. Most of works concentrated on binary problems, where majority and minority class...
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