IEEE - Institute of Electrical and Electronics Engineers, Inc. - A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

Author(s): M. Galar ; A. Fernandez ; E. Barrenechea ; H. Bustince ; F. Herrera
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 July 2012
Volume: 42
Page Count: 22
Page(s): 463 - 484
ISSN (Paper): 1094-6977
ISSN (Online): 1558-2442
DOI: 10.1109/TSMCC.2011.2161285
Regular:

Classifier learning with data-sets that suffer from imbalanced class distributions is a challenging problem in data mining community. This issue occurs when the number of examples that represent... View More

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