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Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets

Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets

Mateo Lopez-Ledezma
Gissel Velarde
ArXiv (abs)PDFHTML

Papers citing "Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets"

3 / 3 papers shown
Title
Tree Boosting Methods for Balanced andImbalanced Classification and their Robustness Over Time in Risk Assessment
Tree Boosting Methods for Balanced andImbalanced Classification and their Robustness Over Time in Risk Assessment
Gissel Velarde
Michael Weichert
Anuj Deshmunkh
Sanjay Deshmane
Anindya Sudhir
K. Sharma
Vaibhav Joshi
183
3
0
25 Apr 2025
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
G. Lemaître
Fernando Nogueira
Christos K. Aridas
84
2,071
0
21 Sep 2016
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
825
39,255
0
09 Mar 2016

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