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Evaluating XGBoost for Balanced and Imbalanced Data: Application to Fraud Detection

Evaluating XGBoost for Balanced and Imbalanced Data: Application to Fraud Detection

Gissel Velarde
Anindya Sudhir
Sanjay Deshmane
Anuj Deshmunkh
K. Sharma
Vaibhav Joshi
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Papers citing "Evaluating XGBoost for Balanced and Imbalanced Data: Application to Fraud Detection"

2 / 2 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
127
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
51
2,052
0
21 Sep 2016