Bing Zhu

23 papers C 1Misc 1Journal 13Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
Aggregate Sales Forecasting Based on Spatial Correlation in Retail.
J. Theor. Appl. Electron. Commer. Res.
Bing Zhu, Zhengqian Sun, Seppe vanden Broucke, Keyi Lan, Duoxi Xiao
2024 Misc conf
A New Hybrid Churn Prediction Model Based on Logistic Regression and Extreme Gradient Boosting.
ICISS
Yongzhen Fan, Guicai Xie, Bing Zhu
2024 — conf
An Interpretable Anomaly Detection Model for Cloud POS Data.
ICMLSC
Lin Gao, Yongzhen Fan, Duoxi Xiao, YuanYuan Li, Bing Zhu, Zhengqian Sun
2024 — conf
Cluster-based Cross-Learning on Decomposed Components: A Novel Framework for SKU Sales Forecasting.
ICAAI
Duoxi Xiao, Jianjun Li, Sen Bai, Yongzhen Fan, Bing Zhu
2023 J jnl
A bagging-based selective ensemble model for churn prediction on imbalanced data.
Expert Syst. Appl.
Bing Zhu, Cheng Qian, Seppe vanden Broucke, Jin Xiao, YuanYuan Li
2023 — conf
Counterfactual learning in customer churn prediction under class imbalance.
ICBDT
YuanYuan Li, Xue Song, Taicheng Wei, Bing Zhu
2022 J jnl
A GAN-based hybrid sampling method for imbalanced customer classification.
Inf. Sci.
Bing Zhu, Xin Pan, Seppe vanden Broucke, Jin Xiao
2021 — conf
A LSTM-cBiGAN based hybrid sampling method for time series customer classification.
DSIT
Xin Pan, Bing Zhu, Yanbing Liu, Feijie Huang
2021 — conf
An Aggregate Store Sales Forecasting Framework based on ConvLSTM.
ICCDA
Yanbing Liu, Keyi Lan, Feijie Huang, Xirong Cao, Boxing Feng, Bing Zhu
2020 J jnl
An Experimental Investigation of Calibration Techniques for Imbalanced Data.
IEEE Access
Lanlan Huang, Junkai Zhao, Bing Zhu, Hao Chen, Seppe K. L. M. vanden Broucke
2020 — conf
Customer classification based on spatial transition probability and Deep Forest.
ACAI
Yanbing Liu, Xiang Shi, Feijie Huang, Senyou Yang, Qiqi Fan, Bing Zhu
2019 J jnl
IRIC: An R library for binary imbalanced classification.
SoftwareX
Bing Zhu, Zihan Gao, Junkai Zhao, Seppe K. L. M. vanden Broucke
2018 J jnl
Benchmarking sampling techniques for imbalance learning in churn prediction.
J. Oper. Res. Soc.
Bing Zhu, Bart Baesens, Aimée Backiel, Seppe K. L. M. vanden Broucke
2017 J jnl
A new transferred feature selection algorithm for customer identification.
Neural Comput. Appl.
Bing Zhu, Yongge Niu, Jin Xiao, Bart Baesens
2017 J jnl
An empirical comparison of techniques for the class imbalance problem in churn prediction.
Inf. Sci.
Bing Zhu, Bart Baesens, Seppe K. L. M. vanden Broucke
2017 — conf
Improving Resampling-based Ensemble in Churn Prediction.
LIDTA@PKDD/ECML
Bing Zhu, Seppe vanden Broucke, Bart Baesens, Sebastián Maldonado
2016 J jnl
Cluster ensemble framework based on the group method of data handling.
Appl. Soft Comput.
Ge-Er Teng, Changzheng He, Jin Xiao, Yue He, Bing Zhu, Xiaoyi Jiang
2015 J jnl
A consistency-based validation for data clustering.
Intell. Data Anal.
Bing Zhu, Changzheng He, Xiaoyi Jiang
2015 J jnl
Customer choice prediction based on transfer learning.
J. Oper. Res. Soc.
Bing Zhu, Changzheng He, Xiaoyi Jiang
2015 — conf
Customers' Risk Type Prediction Based on Analog Complexing.
ITQM
Changzheng He, Bing Zhu, Mingzhu Zhang, Yuanyuan Zhuang, Xiaoli He, Dongyue Du
2012 J jnl
A GMDH-based fuzzy modeling approach for constructing TS model.
Fuzzy Sets Syst.
Bing Zhu, Changzheng He, Panos Liatsis, Xiaoyu Li
2012 J jnl
A robust missing value imputation method for noisy data.
Appl. Intell.
Bing Zhu, Changzheng He, Panos Liatsis
2011 C conf
Using Density based Score Fusion for Multimodal Identification Systems under the Missing Data Scenario.
DeSE
Quang Duc Tran, Panos Liatsis, Bing Zhu, Changzheng He