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Exploratory Under-Sampling for Class-Imbalance Learning

ICDM, pp.965-969, (2006)

Cited by: 1179|Views152
EI WOS SCOPUS

Abstract

Under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. The main deficiency is that many major class examples are ignored. We propose two algorithms to overcome the deficiency. EasyEnsemble samples several subsets from the major class, trains a learner using each of ...More

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