Fuzzy refinement domain adaptation for long term prediction in banking ecosystem

IEEE Transactions on Industrial Informatics

Volumn 10, Issue 2, 2014, Pages 1637-1646

  Behbood, Vahid ^a   Lu, Jie ^a   Zhang, Guangquan ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Bank failure prediction; banking ecosystem; domain adaptation; Machine learning

Indexed keywords

ALGORITHMS; ECOSYSTEMS; EXPERIMENTS; MATHEMATICAL MODELS;

BANK FAILURE PREDICTION; DOMAIN ADAPTATION; LONG-TERM PREDICTION; MACHINE LEARNING METHODS; PREDICTION ACCURACY; PREDICTIVE ACCURACY; REAL-WORLD PROBLEM; REFINEMENT ALGORITHMS;

LEARNING SYSTEMS;

EID: 84900559524     PISSN: 15513203     EISSN: None     Source Type: Journal    
DOI: 10.1109/TII.2012.2232935     Document Type: Article

References (42)

1. D. P. Filev, R. B. Chinnam, F. Tseng, and P. Baruah, "An industrial strength novelty detection framework for autonomous equipment monitoring and diagnostics," IEEE Trans. Ind. Inf., vol. 6, no. 4, pp. 767-779, Nov. 2010.
2. D. Hunter, H. Yu, I. M. S. Pukish, J.Kolbusz, and B.M. Wilamowski, "Selection of proper neural network sizes and architectures: A comparative study," IEEE Trans. Ind. Inf., vol. 8, no. 2, pp. 228-240, May 2012.
3. X. Zhu, Semi-Supervised Learning Literature Survey Computer Science, University of Wisconsin-Madiso. Madison, WI, USA.
4. K. Nigam, A. K.McCallum, S. Thrun, and T.Mitchell, "Text classification from labeled and unlabeled documents using EM," Mach. Learn., vol. 39, pp. 103-134, 2000. (Pubitemid 30594822)
5. T. Joachims, "Transductive inference for text classification using support vector machines," in Proc. 16th Int. Conf. Mach. Learn., Bled, Slovenia, 1999, pp. 200-209.
6. S. Maiti, V. Verma, C. Chakraborty, and Y. Hori, "An adaptive speed sensorless induction motor drive with artificial neural network for stability enhancement," IEEE Trans. Ind. Inf., vol. 8, no. 4, pp. 757-766, Nov. 2012.
7. G. P. C. Fung, J. X. Yu, L. Hongjun, and P. S. Yu, "Text classification without negative examples revisit," IEEE Trans. Knowledge Data Eng., vol. 18, no. 1, pp. 6-20, Jan. 2006. (Pubitemid 43145085)
8. S. J. Pan and Q. Yang, "A survey on transfer learning," IEEE Trans. Knowledge Data En., vol. 22, no. 10, pp. 1345-1359, Oct. 2010.
9. R. Luis, L. Sucar, and E. Morales, "Inductive transfer for learning Bayesian networks," Mach. Learn., vol. 79, pp. 227-255, 2010.
10. A. Arnold, R. Nallapati, and W. W. Cohen, "A comparative study of methods for transductive transfer learning," in Proc. 7th IEEE Int. Conf. Data Mining Workshops, Omaha, NE, USA, 2007, pp. 77-82.
11. E. W. Xiang, C. Bin, D. H. Hu, and Y. Qiang, "Bridging domains using world wide knowledge for transfer learning," IEEE Trans. Knowledge Data Eng., vol. 22, no. 6, pp. 770-783, Jun. 2010.
12. G. Bo, Y. Linjun, X. Chao, and H. Xian-Sheng, "Ranking model adaptation for domain-specific search," IEEE Trans. Knowledge Data Eng., vol. 24, no. 4, pp. 745-758, Apr. 2012.
13. D. Lixin, X. Dong, and I.W. Tsang, "Domain adaptation from multiple sources: A domain-dependent regularization approach," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 3, pp. 504-518, Mar. 2012.
14. D. Lixin, I. W. Tsang, and X. Dong, "Domain transfer multiple kernel learning," IEEE Trans. Pattern Anal. and Mach. Intell., vol. 34, no. 3, pp. 465-479, Mar. 2012.
15. B. Zadrozny, "Learning and evaluating classifiers under sample selection bias," in Proc. 21st Int. Conf. Mach. Learn., Bnaff, Canada, 2004, pp. 114-121.
16. H. Shimodaira, "Improving predictive inference under covariate shift by weighting the log-likelihood function," J. Statist. Plann. Inference, vol. 90, pp. 227-244, 2000.
17. G.-R. Xue, W. Dai, Q. Yang, and Y. Yu, "Topic-bridged PLSA for cross-domain text classification," in Proc. 31st Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, Singapore, 2008, pp. 627-634.
18. J. Quinonero-Candela, M. Sugiyama, A. Schwaighofer, and N. Lawrence, Dataset Shift in Machine Learning. Cambridge, MA, USA: MIT Press, 2009.
19. J. Blitzer, R. McOnald, and F. Pereira, "Domain adaptation with structural correspondence learning," in Proc. Con. Empirical Methods Natural Language Process., Sydney, Australia, 2006, pp. 120-128.
20. J. Blitzer, K. Crammer, A. Kulesza, F. Pereira, and J. Wortman, "Learning bounds for domain adaptation," in Proc. 21st Annu. Conf. Neural Inf. Process. Syst., Cambridge, MA, USA, 2007, pp. 245-252.
21. J. Blitzer, M. Dredze, and F. Pereira, "Biographies, bollywood, boomboxes and blenders: Domain adaptation for sentiment classification," in Proc. 45th Annu.Meeting Assoc. Comput. Ling., Prague, Czech Republic, 2007, pp. 440-447.
22. W. Dai, G.-R. Xue, Q. Yang, and Y. Yu, "Co-clustering based classification for out-of-domain documents," in Proc. 13th ACMSIGKDD Int. Conf. Knowledge Discovery Data Mining, San Jose, CA, USA, 2007, pp. 210-219. (Pubitemid 350229208)
23. Z. Geng, L. Han-Xiong, and G. Min, "Design a wind speed prediction model using probabilistic fuzzy system," IEEE Trans. Ind. Inf., vol. 8, no. 4, pp. 819-827, Nov. 2012.
24. L. Weitao, W. Dianhui, and C. Tianyou, "Flame image-based burning state recognition for sintering process of rotary kiln using heterogeneous features and fuzzy integral," IEEE Trans. Ind. Inf., vol. 8, no. 4, pp. 780-790, Apr. 2012.
25. F. Penedo, R. E. Haber, A. Gajate, and R. M. del Toro, "Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes," IEEE Trans. Ind. Inf., vol. 8, no. 4, pp. 811-818, Nov. 2012.
26. T. Du-Ming, I.Y. Chiang, and T.Ya-Hui, "A shift-tolerant dissimilarity measure for surface defect detection," IEEE Trans. Ind. Inf., vol. 8, no. 1, pp. 128-137, Feb. 2012.
27. T. Cuong and M. M. Trivedi, "3-D posture and gesture recognition for interactivity in smart spaces," IEEE Trans. Ind. Inf., vol. 8, no. 1, pp. 178-187, Feb. 2012.
28. L. Wang, C. Yang, and J. Feng, "On learning with dissimilarity functions," in Proc. Int. Conf. Mach. Learn., Corvallis, OR, 2007, pp. 991-998.
29. M. F. Balcan, A. Blum, and N. Srebro, "A theory of learning with similarity functions," Mach. Learn., vol. 72, pp. 89-112, 2008.
30. D. Xing, W. Dai, G.-R. Xue, and Y. Yu, "Bridged refinement for transfer learning," in Proc. 11th Eur. Conf. Principles Practice Knowledge Discovery Databases, Warsaw, Poland, 2007, pp. 324-335.
31. P. Ferronato, "Architecture for Digital Ecosystems, beyond Service Oriented Architecture," in Proc. IEEE Int. Conf. Digital Ecosyst. Technol., 2007, pp. 660-665. (Pubitemid 47468389)
32. P. Ferronato, "Ecosystem Oriented Architecture (EOA) vs. SOA," in Digital Business Ecosystems. Luxembourg: European Commission, 2007, pp. 111-118.
33. Q. Yang, "Transfer learning beyond text classification," in Proc. 1st Asian Conf. Mach. Learn.: Adv. Mach. Learn., Nanjing, China, 2009, pp. 10-22.
34. L.Wang, M. Sugiyama, C.Yang, K. Hatano, and J. Feng, "Theory and algorithm for learning with dissimilarity functions," Neural Comput., vol. 21, pp. 1459-1484, 2008.
35. L. Page, S. Brin,R.Motwani, andT.Winograd, "The page rank citation ranking: Bringing order to the Web," in Proc. 7th Int. World Wide Web Conf., Brisbane, Australia, 1998, pp. 161-172.
36. W. L. Tung, C. Quek, and P. Cheng, "GenSo-EWS: A novel neuralfuzzy based early warning system for predicting bank failures," Neural Netw., vol. 17, pp. 567-587, 2004. (Pubitemid 38510340)
37. G. S. Ng, C. Quek, and H. Jiang, "FCMAC-EWS: A bank failure early warning system based on a novel localized pattern learning and semantically associative fuzzy neural network," Expert Syst. With Appl., vol. 34, pp. 989-1003, 2008. (Pubitemid 350117470)
38. V. Behbood, J. Lu, and G. Zhang, "Adaptive Inference-based learning and rule generation algorithms in fuzzy neural network for failure prediction," in Proc. IEEE Int. Conf. Intell. Syst. Knowledge Eng. (ISKE), Hangzhou, China, 2010, pp. 33-38.
39. C.-T. Lin and C. S. G. Lee, Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Englewood Cliffs, NJ, USA: Prentice-Hall, 1996.
40. N. Chawla, K. Bowyer, L. Hall, and P. Kegelmeyer, "SMOTE: Synthetic minority over-sampling technique," J. Artif. Intell. Res., vol. 16, pp. 321-357, 2002. (Pubitemid 43057176)
41. W. Wen-June, "New similarity measures on fuzzy sets and on elements," Fuzzy Sets Syst., vol. 85, pp. 305-309, 1997.
42. S. Holm, "A simple sequentially rejective multiple test procedure," Scandinavian J. Statist., vol. 6, pp. 65-70, 1979.