Publication

Journal Paper

  • IRIC: An R library for binary imbalanced classification [code]
    Bing Zhu, Zihan Gao, Junkai Zhao, Seppe Vanden Broucke
    SoftwareX, 2019
  • Benchmarking sampling techniques for imbalance learning in churn prediction
    Bing Zhu, Bart Baesens, Aimée Backiel, Seppe vanden Broucke. Journal of the Operational Research Society, 69 (1):49-65, 2018.
  • 浅谈分类问题中的概率校准 (A brief introduction probability in classification)
    Yao Xiao, Guicai Xie Bing Zhu
    Chinese Statistics, 5, 35-37, 2018
  • An empirical comparison of techniques for class imbalance problem in churn prediction
    Bing Zhu, Bart Baesens, Seppe vanden Broucke
    Information Sciences, 408:84–99, 2017
  • A new transferred feature selection algorithm for customer identification
    Bing Zhu, Yongge Niu, Jin Xiao, Bart Baesens
    Neural Computing and Applications, 28: 2593-2603, 2017
  • The key factors of outstanding credit balances among revolvers: A case study of a bank in China
    Changzheng He, Bing Zhu, Mingzhu Zhang, Xiaoli He
    Procedia Computer Science, 91:341-350, 2016
  • Geer Teng, Changzheng He, Jin Xiao, Yue He, Bing Zhu, Xiaoyi Jiang. Cluster ensemble framework based on the group method of data handling
    Applied Soft Computing, 43:35~46, 2016
  • A consistency-based validation for data clustering
    Bing Zhu, Changzheng He, Xiaoyi Jiang
    Intelligent Data Analysis, 19(3): 471-484, 2015
  • Customer choice prediction based on transfer learning
    Bing Zhu, Changzheng He, Xiaoyi Jiang.
    Journal of the Operational Research Society, 66(6): 1044-1051, 2015
  • 基于迁移学习的客户信用评估模型研究 (Research on credit scoring model based on transfer learning)
    Bing Zhu, Changzheng He, Huiyuan Li
    运筹与管理(Operations Research and Management Science), 24(2): 201-207, 2015
  • Customers’ risk type prediction based on analog complexing
    Changzheng He, Bing Zhu, Mingzhu Zhang, Yuanyuan Zhuang, Xiaoli He, Dongyue Du
    Procedia Computer Science, 55: 939 – 943, 2015
  • 手机银行客户价值定义及其影响因素分析 (Research on the definition of customer value and its influencing factors)
    Xin Wei, Changzheng He, Bing Zhu
    软科学 (Soft Science) , 20, 93-96, 2015
  • Using group method of data handling to model customer choice behaviour
    Bing Zhu, Changzheng He, Yongge Niu
    Scientia Iranica, 21(3): 1051-1060, 2014
  • One-step dynamic classifier ensemble model for customer value segmentation with missing values
    Jin Xiao, Bing Zhu, Geer Teng, Changzheng He, Dunhu Liu Mathematical Problems in Engineering, 1:1-15, 2014
  • 基于序关系重构的恒定再平衡投资组合 (Rank-reconstruction based constant rebalanced portfolios)
    Xuwei Liu, Changzheng He, Bing Zhu
    中国管理科学 (Chinese Journal of Management Science), 22(3): 13-19, 2014
  • Changzheng He, Li Kong, Bing Zhu, Jin Xiao,信用卡取现影响因素研究(Research on the factors that influence cash withdrawal from credit card. 管理评论 (Management Review) , 10:30-45, 2014.
  • D-GMDH: A novel inductive modelling approach in the forecasting of the industrial economy
    Mingzhu Zhang, Changzheng He, Xin Gu, Panos Liatsis, Bing Zhu
    Economic Modelling, 30:514-520, 2013
  • A GMDH-based fuzzy modeling approach for constructing TS model
    Bing Zhu, Changzheng He, Panos Liatsis, Xiaoyu Li
    Fuzzy Sets and Systems, 189 (1) :19-29, 2012
  • A robust missing value imputation method for noisy data
    Bing Zhu, Changzheng He, Panos Liatsis
    Applied Intelligence, 36(1): 61-74, 2012

Conference Paper

  • A hybrid deep learning model for consumer credit scoring
    Bing Zhu, Wenchuan Yang, Huaxuan Wang, Yuan Yuan
    Proceeding of 2018 International Conference on Machine Learning Technologies, pp.205-208, 2018
  • Investigating decision tree in churn prediction with class imbalance
    Bing Zhu, Guicai Xie, Yuan Yuan,Yiqin Duan
    Proceeding of 2018 International Conference on Data Processing and Applications,pp.11-15, 2018
  • Improving resampling-based ensemble in churn prediction
    Bing Zhu, Seppe vanden Broucke, Bart Baesens, Sebastian Maldonado
    Proceedings of the International Conference on Management Science and Engineering management, LIDTA (Learning With Imbalanced Domains: Theory and Applications) Workshop of ECML/PKDD, pp. 79-91, 2017
  • A balanced transfer learning model for customer churn prediction
    Bing Zhu, Jin Xiao, Changzheng He
    Proceedings of the International Conference on Management Science and Engineering management,  pp. 97-104, 2014
  • A new hybrid model of feature selection for imbalanced data
    Bing Zhu, Qingqing Deng, Xiaozhou He
    Proceeding of the International Conference on Management Science and Engineering Management,  pp. 238-242, 2013
  • An approach for multimodal biometric fusion under the missing data scenario
    Tran Quang Duc, Liatsis Panos, Bing Zhu, Changzheng He
    Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE 2011) , pp. 185-188, 2011
  • Using density based score fusion for multimodal identification systems under the missing data scenario
    Tran Quang Duc, Panos Liatsis , Bing Zhu, Changzheng He
    Proceeding of Developments in E-systems Engineering (DeSE), pp. 238-242, 2011
  • A new imputation method based on GMDH
    Changzheng He, Bing Zhu
    Proceedings of IWIM2009, pp. 14-19, Krynica, Poland, 2009.
  • TS-based GMDH model and its application
    Changzheng He, Bing Zhu
    International Conference on Inductive Modelling(ICIM2008), pp. 31-33, Kiev, Ukraine, 2008.