Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations

Fuzzy Sets and Systems

Volumn 161, Issue 23, 2010, Pages 3064-3080

  Fernández, Alberto ^a   Calderón, María ^b   Barrenechea, Edurne ^b   Bustince, Humberto ^b   Herrera, Francisco ^c  

^a UNIVERSITY OF JAÉN   (Spain)

^b PUBLIC UNIVERSITY OF NAVARRE   (Spain)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

Fuzzy preference relations; Fuzzy rule based classification systems; Multi class problems; Multi classifiers; Pairwise learning

Indexed keywords

FUZZY PREFERENCE RELATIONS; FUZZY RULE-BASED CLASSIFICATION SYSTEMS; MULTI-CLASS PROBLEMS; MULTI-CLASSIFIERS; PAIRWISE LEARNING;

CLASSIFIERS; FUZZY RULES; FUZZY SETS; LINGUISTICS; STATISTICAL TESTS;

FUZZY INFERENCE;

EID: 77957869952     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fss.2010.05.016     Document Type: Article

References (36)

1. M.R. Akbarzadeh-Totonchi, and M. Moshtagh-Khorasani A hierarchical fuzzy rule-based approach to aphasia diagnosis Journal of Biomedical Informatics 40 5 2007 465 475 (Pubitemid 47332337)
2. J. Alcalá-Fdez, L. Sánchez, S. García, M. del Jesus, S. Ventura, J. Garrell, J. Otero, C. Romero, J. Bacardit, V. Rivas, J. Fernández, and F. Herrera KEEL: a software tool to assess evolutionary algorithms to data mining problems Soft Computing 13 3 2009 307 318
3. E.L. Allwein, R.E. Schapire, and Y. Singer Reducing multiclass to binary: a unifying approach for margin classifiers Journal of Machine Learning Research 1 2000 113 141 (Pubitemid 33738778)
4. A. Asuncion, D.J. Newman, UCI machine learning repository, University of California, Irvine, School of Information and Computer Sciences. URL: 〈 http://www.ics.uci.edu/∼mlearn/MLRepository.html 〉, 2007.
5. O. Cordón, M.J. del Jesus, and F. Herrera A proposal on reasoning methods in fuzzy rule-based classification systems International Journal of Approximate Reasoning 20 1 1999 21 45
6. O. Cordón, F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena Ten years of genetic fuzzy systems: current framework and new trends Fuzzy Sets and Systems 141 1 2004 5 31
7. J. Demšar Statistical comparisons of classifiers over multiple data sets Journal of Machine Learning Research 7 2006 1 30 (Pubitemid 43022939)
8. T.G. Dietterich An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization Machine Learning 40 2000 139 157
9. A. Fernández, M.J. del Jesus, and F. Herrera On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets Information Sciences 180 18 2010 1268 1291
10. A. Fernández, S. García, M.J. del Jesus, and F. Herrera A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets Fuzzy Sets and Systems 159 18 2008 2378 2398
11. J. Fürnkranz Round robin classification Journal of Machine Learning Research 2 2002 721 747 (Pubitemid 135712579)
12. J. Fürnkranz, E. Hüllermeier, and S. Vanderlooy Binary decomposition methods for multipartite ranking W.L. Buntine, M. Grobelnik, D. Mladenic, J. Shawe-Taylor, ECML/PKDD (1) of Lecture Notes in Computer Science Vol. 5781 2009 Springer 359 374
13. S. García, A. Fernández, J. Luengo, and F. Herrera A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability Soft Computing 13 10 2009 959 977
14. S. García, A. Fernández, J. Luengo, and F. Herrera Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power Information Sciences 180 10 2010 2044 2064
15. S. García, and F. Herrera An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons Journal of Machine Learning Research 9 2008 2677 2694
16. A. González, and R. Pérez A learning system of fuzzy control rules F. Herrera, J.L. Verdegay, Genetic Algorithms and Soft Computing 1996 Physica-Verlag New York 202 225
17. A. González, and R. Pérez Completeness and consistency conditions for learning fuzzy rules Fuzzy Sets and Systems 96 1998 37 51 (Pubitemid 128654845)
18. A. González, and R. Pérez SLAVE: a genetic learning system based on an iterative approach IEEE Transactions on Fuzzy Systems 7 1999 176 191
19. A. González, and R. Pérez Selection of relevant features in a fuzzy genetic learning algorithm IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 31 3 2001 417 425 (Pubitemid 32676847)
20. T. Hastie, and R. Tibshirani Classification by pairwise coupling The Annals of Statistics 26 2 1998 451 471 (Pubitemid 128089819)
21. F. Herrera Genetic fuzzy systems: taxonomy, current research trends and prospects Evolutionary Intelligence 1 2008 27 46
22. J.C. Hühn, and E. Hüllermeier FR3: a fuzzy rule learner for inducing reliable classifiers IEEE Transactions on Fuzzy Systems 17 1 2009 138 149
23. E. Hüllermeier, and K. Brinker Learning valued preference structures for solving classification problems Fuzzy Sets and Systems 159 18 2008 2337 2352
24. E. Hüllermeier, J. Fürnkranz, Comparison of ranking procedures in pairwise preference learning. In: Proceedings of the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU04, Vol. 11, 2004.
25. E. Hüllermeier, and S. Vanderlooy Combining predictions in pairwise classification: an optimal adaptive voting strategy and its relation to weighted voting Pattern Recognition 43 1 2010 128 142
26. H. Ishibuchi, and T. Nakashima Effect of rule weights in fuzzy rule-based classification systems IEEE Transactions on Fuzzy Systems 9 4 2001 506 515 (Pubitemid 32935694)
27. H. Ishibuchi, T. Nakashima, and M. Nii Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining 2004 Springer-Verlag
28. H. Ishibuchi, and T. Yamamoto Rule weight specification in fuzzy rule-based classification systems IEEE Transactions on Fuzzy Systems 13 2005 428 435 (Pubitemid 41461439)
29. H. Ishibuchi, T. Yamamoto, and T. Nakashima Hybridization of fuzzy GBML approaches for pattern classification problems IEEE Transactions on System, Man and Cybernetics B 35 2 2005 359 365 (Pubitemid 40535918)
30. J. Marín-Blázquez, and G.M. Pérez Intrusion detection using a linguistic hedged fuzzy-XCS classifier system Soft Computing 13 3 2009 273 290
31. S. Orlovsky Decision-making with a fuzzy preference relation Fuzzy Sets and Systems 1 1978 155 167
32. D. Sheskin Handbook of Parametric and Nonparametric Statistical Procedures second ed. 2006 Chapman & Hall/CRC
33. Y. Sun, A.C. Wong, and M.S. Kamel Classification of imbalanced data: a review International Journal of Pattern Recognition and Artificial Intelligence 23 4 2009 687 719
34. C. Tsang, S. Kwong, and H. Wang Genetic-fuzzy rule mining approach and evaluation of feature selection techniques for anomaly intrusion detection Pattern Recognition 40 9 2007 2373 2391 (Pubitemid 46669583)
35. G. Venturini SIA: a supervised inductive algorithm with genetic search for learning attributes based concepts P. Brazdil, Machine Learning ECML - 93 of Lecture Notes in Artificial Intelligence Vol. 667 1993 Springer 280 296
36. H. Wu, and J. Mendel Classification of battlefield ground vehicles using acoustic features and fuzzy logic rule-based classifiers IEEE Transactions on Fuzzy Systems 15 1 2007 56 72 (Pubitemid 46444304)