Test-cost-sensitive attribute reduction

Information Sciences

Volumn 181, Issue 22, 2011, Pages 4928-4942

  Min, Fan ^a   He, Huaping ^b   Qian, Yuhua ^c   Zhu, William ^a  

^a MINNAN NORMAL UNIVERSITY   (China)

^b SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING   (China)

^c BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Attribute reduction; Cost sensitive learning; Heuristic algorithm; Test cost

Indexed keywords

ATTRIBUTE REDUCTION; CLASSIFICATION ACCURACY; COST-SENSITIVE LEARNING; DATA SETS; MACHINE LEARNING APPLICATIONS; PARAMETER SET; POTENTIAL APPLICATIONS; PRE-PROCESSING; REDUCTION ALGORITHMS; RESEARCH TRENDS; TEST COST; UNIVERSITY OF CALIFORNIA; WORK FOCUS;

ENGINEERING RESEARCH; HEURISTIC ALGORITHMS; ROUGH SET THEORY; TESTING;

COST REDUCTION;

EID: 79960290370     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2011.07.010     Document Type: Article

References (56)

1. Generating Gaussian random numbers. .
2. Wikipedia. .
3. J.G. Bazan, A. Skowron, Dynamic reducts as a tool for extracting laws from decision tables, in: ISMIS'94, Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems, 1994.
4. J.G. Bazan, M. Szczuka, The RSES homepage, 1994-2005. .
5. J.G. Bazan, M.S. Szczuka, RSES and RSESlib - a collection of tools for rough set computations., in: Rough Sets and Current Trends in Computing, LNCS, vol. 2005, 2000, pp. 106-113.
6. C.L. Blake, C.J. Merz, UCI repository of machine learning databases, 1998. .
7. D. Chen, C. Wang, and Q. Hu A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets Information Sciences 177 17 2007 3500 3518
8. M. Dash, and H. Liu Consistency-based search in feature selection Artificial Intelligence 151 2003 155 176
9. D. Deng Parallel reduct and its properties Granular Computing 2009 121 125
10. D. Deng, J. Wang, and X. Li Parallel reducts in a series of decision subsystems Computational Sciences and Optimization 2 2009 377 380
11. P. Domingos, and M. Pazzani On the optimality of the simple Bayesian classifier under zero-one loss Machine Learning 29 1997 103 130 (Pubitemid 127510035)
12. W. Fan, S. Stolfo, J. Zhang, P. Chan, Adacost: Misclassification cost-sensitive boosting, in: Proceedings of the 16th International Conference on Machine Learning, 1999, pp. 97-105.
13. U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth From data mining to knowledge discovery in databases AI Magazine 17 1996 37 54
14. J.H. Friedman, and W. Stuetzle Projection pursuit regression Journal of the American Statistics Association 76 1981 817 823
15. J.J. Grefenstette Optimization of control parameters for genetic algorithms IEEE Transactions on Systems, Man, and Cybernetics 1986 122 128 (Pubitemid 16187857)
16. M. Harchol-Balter Task assignment with unknown duration Journal of the ACM 49 2002 260 288 (Pubitemid 44159322)
17. K. Hornik, M. Stinchcombe, and H. White Multilayer feedforward networks are universal approximators Neural Networks 2 5 1989 359 366 (Pubitemid 20609008)
18. Q. Hu, W. Pan, S. An, P. Ma, and J. Wei An efficient gene selection technique for cancer recognition based on neighborhood mutual information International Journal of Machine Learning and Cybernetics 1 1-4 2010 63 74
19. E.B. Hunt, J. Marin, and P.J. Stone Experiments in Induction 1966 Academic Press New York
20. R. Jensen, and Q. Shen Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches IEEE Transactions on Knowledge and Data Engineering 16 12 2004 1457 1471 (Pubitemid 40010921)
21. Q. Liu, L. Chen, J. Zhang, and F. Min Knowledge reduction in inconsistent decision tables Advanced Data Mining and Applications 4093/2006 2006 626 635 (Pubitemid 44503205)
22. Q. Liu, F. Li, F. Min, M. Ye, and G. Yang An efficient reduction algorithm based on new conditional information entropy Control and Decision (in Chinese) 20 8 2005 878 882 (Pubitemid 41293160)
23. Z. Meng, and Z. Shi A fast approach to attribute reduction in incomplete decision systems with tolerance relation-based rough sets Information Sciences 179 16 2009 2774 2793
24. F. Min, X. Du, H. Qiu, and Q. Liu Minimal attribute space bias for attribute reduction Rough Set and Knowledge Technology 2007 379 386 (Pubitemid 350270231)
25. F. Min, and Q. Liu A hierarchical model for test-cost-sensitive decision systems Information Sciences 179 14 2009 2442 2452
26. F. Min, Q. Liu, H. Tan, and L. Chen The M-relative reduct problem Rough Set and Knowledge Technology 2006 170 175 (Pubitemid 44165637)
27. F. Min, W. Zhu, Coser: Cost-senstive rough sets, 2011. .
28. Z. Pawlak Rough sets International Journal of Computer and Information Sciences 11 1982 341 356
29. Z. Pawlak Rough sets and intelligent data analysis Information Sciences 147 12 2002 1 12 (Pubitemid 35349784)
30. Y. Qian, J. Liang, W. Pedrycz, and C. Dang Positive approximation: an accelerator for attribute reduction in rough set theory Artificial Intelligence 174 9-10 2010 597 618
31. J.R. Quinlan Induction of decision trees Machine Learning 1 1986 81 106
32. J.R. Quinlan C4.5 Programs for Machine Learning 1993 Morgan Kaufmann Publisher San Mateo, California
33. A. Skowron, C. Rauszer, The discernibility matrics and functions in information systems, in: Intelligent Decision Support, 1992.
34. R. Susmaga Computation of minimal cost reducts Foundations of Intelligent Systems LNCS vol. 1609 1999 Springer 448 456
35. D. Tong, and R. Mintram Genetic algorithm-neural network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection International Journal of Machine Learning and Cybernetics 1 1-4 2010 75 87
36. P.D. Turney Cost-sensitive classification: empirical evaluation of a hybrid genetic decision tree induction algorithm Journal of Artificial Intelligence Research 2 1995 369 409
37. V. Vapnik, and A. Chervonenkis On the uniform convergence of relative frequencies of events to their probabilities Theory of Probability and Its Application 16 2 1971 264 280
38. G. Wang, Attribute core of decision table, in: Rough Sets and Current Trends in Computing, LNCS, vol. 2475, 2002, pp. 213-217.
39. G. Wang, H. Yu, and D. Yang Decision table reduction based on conditional information entropy Chinese Journal of Computers 2 7 2002 759 766 (Pubitemid 35339183)
40. X.-Z. Wang, and C.-R. Dong Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy IEEE Transactions on Fuzzy Systems 17 3 2009 556 567
41. X.-Z. Wang, J.-H. Zhai, and S.-X. Lu Induction of multiple fuzzy decision trees based on rough set technique Information Sciences 178 16 2008 3188 3202
42. J. Wróblewski, Finding minimal reducts using genetic algorithms, in: International Workshop on Rough Sets Soft Computing at Second Annual Joint Conference on Information Sciences, 1995, pp. 186-189.
43. X. Wu, V. Kumar, J.R. Quinlan, J. Ghosh, Q. Yang, H. Motoda, G.J. McLachlan, A. Ng, B. Liu, P.S. Yu, Z. Zhou, M. Steinbach, D.J. Hand, and D. Steinberg Top 10 algorithms in data mining Knowledge Information Systems 14 2008 1 37
44. C. Xu, F. Min, Weighted reduction for decision tables, in: Fuzzy Systems and Knowledge Discovery, 2006, pp. 246-255. (Pubitemid 44670720)
45. C. Xu, and F. Min Weighted reduction and its application in automatic correction of chinese part-of-speech tagging (in Chinese) Control and Decision 22 7 2007 744 747
46. Y. Yao, and Y. Zhao Attribute reduction in decision-theoretic rough set models Information Sciences 178 17 2008 3356 3373
47. Y. Yao, Y. Zhao, J. Wang, On reduct construction algorithms, in: Rough Set and Knowledge Technology, 2006, pp. 297-304. (Pubitemid 44165655)
48. W. Yi, M. Lu, and Z. Liu Multi-valued attribute and multi-labeled data decision tree algorithm International Journal of Machine Learning and Cybernetics 2 2 2011 67 74
49. W. Zhang, J. Mi, and W. Wu Knowledge reductions in inconsistent information systems Chinese Journal of Computers 26 1 2003 12 18
50. K. Zhao, and J. Wang A reduction algorithm meeting users' requirements Journal of Computer Science and Technology 17 2002 578 593
51. Y. Zhao, F. Lou, S. Wong, Y. Yao, A general definition of an attribute reduct, in: Rough Sets and Knowledge Technology, LNAI, vol. 4481, 2007, pp. 101-108. (Pubitemid 350270200)
52. Z. Zhou, and X. Liu Training cost-sensitive neural networks with methods addressing the class imbalance problem IEEE Transactions on Knowledge and Data Engineering 18 1 2006 63 77 (Pubitemid 43145089)
53. J. Zhu, X. Li, and W. Shen Effective genetic algorithm for resource-constrained project scheduling with limited preemptions International Journal of Machine Learning and Cybernetics 2011 1 11
54. W. Zhu, and F. Wang Reduction and axiomization of covering generalized rough sets Information Sciences 152 1 2003 217 230
55. W. Zhu, and F. Wang On three types of covering rough sets IEEE Transactions on Knowledge and Data Engineering 19 8 2007 1131 1144
56. W. Ziarko Variable precision rough set model Journal of Computer and System Sciences 46 1 1993 39 59 (Pubitemid 23639120)