Research on the Classification of Commercial Banks’ Fund Clients Based on Learning with Label Proportions

Procedia Computer Science - Tập 91 - Trang 988-994 - 2016
Fuhai Ma1,2,3,4, Yong Shi1,2,3, Bo Wang1,2,3, Zhensong Chen1,2,3
1Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing 100190, China
2School of Management, Chinese Academy of Sciences, Beijing, 100190, China
3Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing, 100190, China
4University of Nebraska Omaha, Omaha, NE 68106 USA

Tài liệu tham khảo

Hu, 2003, A fuzzy-based customer classification method for demand-responsive logistical distribution operations[J], Fuzzy Sets and Systems, 139, 431, 10.1016/S0165-0114(02)00516-X Chen, 2003, Constructing a multi-valued and multi-labeled decision tree[J], Expert Systems with Applications, 25, 199, 10.1016/S0957-4174(03)00047-2 Shin, 2004, Segmentation of stock trading clients according to potential value[J], Expert systems with applications, 27, 27, 10.1016/j.eswa.2003.12.002 Chicco, 2006, Comparisons among clustering techniques for electricity customer classification[J], Power Systems, IEEE Transactions on, 21, 933, 10.1109/TPWRS.2006.873122 Gaber, 2006, Detection and classification of changes in evolving data streams[J], International Journal of Information Technology & Decision Making, 5, 659, 10.1142/S0219622006002179 Glover, 2006, New optimization models for data mining[J], International Journal of Information Technology & Decision Making, 5, 605, 10.1142/S0219622006002143 López J J, Aguado J A, Martín F, et al. Electric customer classification using Nopfield recurrent ANN[C]//Electricity Market, 2008. EEM 2008. 5th International Conference on European. IEEE, 2008: 1-6. Wu, 2011, Customer segmentation of multiple category data in e-commerce using a soft-clustering approach[J], Electronic Commerce Research and Applications, 10, 331, 10.1016/j.elerap.2010.11.002 Chen Bocheng, 2004, etc. An Application of SOM Neural Network in Customer Classification [J].systems Engineering-Theory & Practice, 3, 8 Xiao Jin, 2008, The Structure Learning of Bayesian Classifier Based on SODM and Its Application in Customer Classification [J], Journal of Management Sciences, 21, 54 N. Quadrianto, A.J. Smola, T.S. Caetano, Q.V. Le, Estimating labelsfrom label proportions, The Journal of Machine Learning Research 10(2009) 2349{2374. Lai K T, Yu F X, Chen M S, et al. Video event detection by inferring temporal instance labels[C]//Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014: 2251-2258. M. Stolpe, K. Morik, Learning from label proportions by optimizingcluster model selection, in: Machine Learning and Knowledge Discoveryin Databases, Springer, 2011, pp. 349{364. G. Patrini, R. Nock, T. Caetano, P. Rivera, (almost) no label no cry, in:Advances in Neural Information Processing Systems, 2014, pp. 190{198. S. Rueping, Svm classier estimation from group probabilities, in: Proceedings of the 27th International Conference on Machine Learning(ICML-10), 2010, pp. 911{918.