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Big data,Feature Importance,Feature Selection,Class Imbalance,Machine Learning,Random Undersampling,ECBDL’14,Slowloris,POST
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https://doi.org/10.1186/s40537-019-0231-2
Springer International Publishing
Journal of Big Data, https://doi.org/10.1186/s40537-019-0231-2
Big data
Feature Importance
Feature Selection
Class Imbalance
Machine Learning
Random Undersampling
ECBDL’14
Slowloris
POST
Examining characteristics of predictive models with imbalanced big data
Tawfiq Hasanin
Taghi M. Khoshgoftaar
Joffrey L. Leevy
Naeem Seliya
10.1186/s40537-019-0231-2
2010-04-23
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