CLASSIFICATION OF IMBALANCED DATA: A REVIEW
作者： YANMIN SUN , ANDREW K. C. WONG , MOHAMED S. KAMEL
DOI: 10.1142/S0218001409007326
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摘要: Classification of data with imbalanced class distribution has encountered a significant drawback of the performance attainable by most standard classifier learning algorithms which assume a relatively balanced class distribution and equal misclassification costs. This paper provides a review of the classification of imbalanced data regarding: the application domains; the nature of the problem; the learning difficulties with standard classifier learning algorithms; the learning objectives and evaluation measures; the reported research …
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