Severely imbalanced Big Data challenges: investigating data sampling approaches

Severely imbalanced Big Data challenges: investigating data sampling approaches

Abstract Severe class imbalance between majority and minority classes in Big Data can bias the predictive performance of Machine Learning algorithms toward the majority (negative) class. Where the minority (positive) class holds greater value than the majority (negative) class and the occurrence of...

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Bibliographic Details
Main Authors: Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy, Richard A. Bauder
Format: Article
Language:English
Published: SpringerOpen 2019-11-01
Series:Journal of Big Data
Subjects:
Big Data
Class imbalance
Machine Learning
Medicare fraud
Oversampling
SlowlorisBig
Online Access:https://doi.org/10.1186/s40537-019-0274-4

Internet

https://doi.org/10.1186/s40537-019-0274-4

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