Compactness rate as a rule selection index based on Rough Set Theory to improve data analysis for personal investment portfolios

Applied Soft Computing Journal

Volumn 11, Issue 4, 2011, Pages 3671-3679

  Shyng, Jhieh Yu ^a   Shieh, How Ming ^b   Tzeng, Gwo Hshiung ^c,d  

^a LAN YANG INSTITUTE OF TECHNOLOGY   (Taiwan)

^b NATIONAL CENTRAL UNIVERSITY   (Taiwan)

^c KAINAN UNIVERSITY   (Taiwan)

^d NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

Compactness rate; Investment portfolio; Rough Set Theory (RST); Strength rate; Support

Indexed keywords

COMPACTNESS RATE; CRITICAL PROBLEMS; DATA ANALYSIS; DECISION MAKERS; DECISION RULES; INTERESTING RULES; INVESTMENT PORTFOLIO; ROUGH SET; RULE SELECTION; SELECTION INDEXES; STRENGTH RATE;

DATA REDUCTION; DECISION MAKING; DECISION THEORY; INVESTMENTS;

ROUGH SET THEORY;

EID: 79954572821     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.01.038     Document Type: Article

References (29)

1. M. Beynon, and M. Peel Variable precision rough set theory and data discretisation: an application to corporate failure prediction Omega 29 6 2001 561 576 (Pubitemid 33628771)
2. A.I. Dimitras, R. Slowinski, R. Susmaga, and C. Zopounidis Business failure prediction using rough sets European Journal of Operational Research 114 2 1999 263 280
3. S. Greco, B. Matarazzo, and R. Slowinski Rough sets theory for multicriteria decision analysis European Journal of Operational Research 129 1 2001 1 47 (Pubitemid 32071221)
4. K. Hanisch Reasons people retire and their relations to attitudinal and behavioral correlates in retirement Journal of Vocational Behavior 45 1 1994 1 16
5. T. Harrison Understanding the behaviour of financial services consumers: a research agenda Journal of Financial Service Marketing 8 1 2003 6 9
6. T. Hennig-Thuran, and K. Klee The impact of customer satisfaction and relationship quality on customer retention: a critical reassessment and model development Psychology and Marketing 14 8 1997 797-764
7. Y. Hu, R. Chen, and G. Tzeng Finding fuzzy classification rules using data mining techniques Pattern Recognition Letters 24 1-3 2003 509 519 (Pubitemid 36080792)
8. H. Li, and M. Chen Induction of multiple criteria optimal classification rules for biological and medical data Computers in Biology and Medicine 38 2008 42 52 (Pubitemid 350250786)
9. H. Markowitz Portfolio selection Journal of Finance Paper 7 1 1952 77 91
10. Z. Pawlak Rough sets International Journal of Computer and Information Science 11 5 1982 341 356
11. Z. Pawlak Rough classification International Journal of Man-Machine Studies 20 5 1984 469 483 (Pubitemid 15102839)
12. Z. Pawlak Rough sets, decision algorithms and Bayes' theorem European Journal of Operational Research 136 1 2002 181 189 (Pubitemid 33018811)
13. D Plath, and H. Stevenson Financial services consumption behavior across Hispanic American consumers Journal of Business Research 58 8 2005 1089 1099 (Pubitemid 40131360)
14. B. Predki, R. Slowinski, J. Stefanowski, R. Susmaga, and S. Wilk ROSE - Software Implementation of the Rough Set Theory L. Polkowski, A. Skowron, Rough Sets and Current Trends in Computing, Proc. RSCTC'98, Lecture Notes in Artificial Intelligence, vol. 1424 1998 Springer Berlin 605 608 (Pubitemid 128093468)
15. J. Shyng, F. Wang, G. Tzeng, and K. Wu Rough set theory in analyzings the attributes of combination values for the insurance market Expert System with Application 32 1 2007 56 64 (Pubitemid 44311465)
16. J. Shyng, G. Tzeng, S. Hsieh, and F. Wang Data mining for multi-domain decision-making based on Rough Set Theory IEEE International Conference on Systems, Man, and Cybernetics Taipei, Taiwan 2006
17. M. Teichman, P. Cecconi, B. Bernheim, N. Novarro, M. Monga, D. DaRosa, and M. Resnick How do residents manage personal finances? The American Journal of Surgery 189 2 2005 134 139 (Pubitemid 40255101)
18. T. Beaubouefa, F.E. Petryb, and R. Ladnerb Spatial data methods and vague regions: a rough set approach Applied Soft Computing 7 1 2007 425 440
19. X. Shaoa, X. Chua, H. Qiua, L. Gaoa, and J. Yanb An expert system using rough sets theory for aided conceptual design of ship's engine room automation Expert Systems with Applications 36 2 2009 3223 3233
20. J. Shyng, H. Shieh, G. Tzeng, and S. Hsieh Using FSBT technique with Rough Set Theory for personal investment portfolio analysis European Journal of Operational Research 201 2010 601 607
21. B. Walczak, and D. Massart Tutorial rough sets theory Chemometrics and Intelligent Laboratory Systems 47 1 1999 1 16
22. The Wall Street Journal, http://asia.wsj.com/home-page.
23. Dalal Street Investment Journal, http://www.dalalstreetjournal.com.
24. J. Han, and M. Kamber Data Mining: Concepts and Techniques 2001 Simon Fraser University, Morgan Kaufmann Publishers San Francisco
25. D. Grzymala-Busse, and J. Grzymala-Busse On the usefulness of machine learning approach to knowledge acquisition Computational Intelligence 11 2 1995 268 279
26. R. Quinlan Induction of decision trees Machine Learning 1 1 1986 81 106
27. L. Zadeh Fuzzy sets Information and Control 8 3 1965 338 353
28. R. Li, and Z. Wang Mining classification rules using rough sets and neural networks European Journal of Operational Research 157 2 2004 439 448
29. C. Cheng, T. Chen, and L. Wei A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting Information Sciences 180 9 2010 1610 1629