Evolutionary undersampling for extremely imbalanced big data classification under apache spark

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Evolutionary undersampling for extremely imbalanced big data classification under apache spark

The classification of datasets with a skewed class distribution is an important problem in data mining. Evolutionary undersampling of the majority class has proved to be a successful approach to tackle this issue. Such a challenging task may become even more difficult when the number of the majority...

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Bibliographic Details
Main Authors:	Triguero, Isaac, Galar, M., Merino, D., Maillo, Jesus, Bustince, H., Herrera, Francisco
Format:	Conference or Workshop Item
Published:	2016
Subjects:	Big data Sparks Data mining Data models Biological cells Proposals Standards
Online Access:	https://eprints.nottingham.ac.uk/38876/

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