15 citations · 19 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 15 cited
Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost
Chen Wang, Chengyuan Deng, Suzhen Wang
The paper presents Imbalance-XGBoost, a Python package that combines the powerful XGBoost software with weighted and focal losses to tackle binary label-imbalanced classification t…
stat.ME2018★ 4 cited
Robust Propensity Score Computation Method based on Machine Learning with Label-corrupted Data
Chen Wang, Suzhen Wang, Fuyan Shi +1
In biostatistics, propensity score is a common approach to analyze the imbalance of covariate and process confounding covariates to eliminate differences between groups. While ther…