Fuzzy-Rough-Set-Based Active Learning

IEEE Transactions on Fuzzy Systems

Volumn 22, Issue 6, 2014, Pages 1699-1704

  Wang, Ran ^a   Chen, Degang ^b   Kwong, Sam ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Active learning; fuzzy rough set; inconsistency; sample covering; support vector machine (SVM)

Indexed keywords

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; SUPPORT VECTOR MACHINES;

ACTIVE LEARNING; ACTIVE LEARNING SCHEME; FUZZY-ROUGH SETS; GAUSSIAN KERNELS; INCONSISTENCY; LOWER APPROXIMATION; SIMILARITY RELATIONS; UNLABELED SAMPLES;

ROUGH SET THEORY;

EID: 84911394317     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2013.2291567     Document Type: Article

References (23)

1. S. Tong and D. Koller, "Support vector machine active learning with applications to text classification," J. Mach. Learn. Res., vol. 2, pp. 45-66, 2002.
2. R. Wang, S. Kwong, and D. Chen, "Inconsistency-based active learning for support vector machines," Pattern Recog., vol. 45, no. 10, pp. 3751-3767, 2012.
3. Y. Freund, H. S. Seung, E. Shamir, and N. Tishby, "Selective sampling using the query by committee algorithm," Mach. Learn., vol. 28, no. 2, pp. 133-168, 1997.
4. D. Chen, L. Zhang, S. Zhao, Q. Hu, and P. Zhu, "A novel algorithm for finding reducts with fuzzy rough sets," IEEE Trans. Fuzzy Syst., vol. 20, no. 2, pp. 385-389, Apr. 2012.
5. D. S. Yeung, D. Chen, E. C. C. Tsang, J. Lee, and X. Z. Wang, "On the generalization of fuzzy rough sets," IEEE Trans. Fuzzy Syst., vol. 13, no. 3, pp. 343-361, Jun. 2005.
6. S. Zhao, E. C. C. Tsang, and D. Chen, "The model of fuzzy variable precision rough sets," IEEE Trans. Fuzzy Syst., vol. 17, no. 2, pp. 451-467, Apr. 2009.
7. E. C. C. Tsang, D. Chen, D. S. Yeung, X. Z. Wang, and J. Lee, "Attributes reduction using fuzzy rough sets," IEEE Trans. Fuzzy Syst., vol. 16, no. 5, pp. 1130-1141, Oct. 2008.
8. S. Zhao, E. C. C. Tsang, D. Chen, and X. Z. Wang, "Building a rule-based classifier - A fuzzy-rough set approach," IEEE Trans. Knowl. Data Eng., vol. 22, no. 5, pp. 624-638, May 2010.
9. N. Mac Parthaláin and R. Jensen, "Fuzzy-rough set based semi-supervised learning," in Proc. IEEE Int. Conf. Fuzzy Syst., 2011, pp. 2465-2472.
10. Z. Xue, Y. Shang, and A. Feng, "Semi-supervised outlier detection based on fuzzy rough c-means clustering," Math. Comput. Simul., vol. 80, no. 9, pp. 1911-1921, 2010.
11. R. Wang, S. Kwong, D. Chen, and Q. He, "Fuzzy rough sets based uncertainty measuring for stream based active learning," in Proc. Int. Conf. Mach. Learn. Cybern., 2012, pp. 282-288.
12. D. Dubois and H. Prade, "Putting rough sets and fuzzy sets together," Intell. Decis. Supp., vol. 11, pp. 203-232, 1992.
13. A. M. Radzikowska and E. E. Kerre, "A comparative study of fuzzy rough sets," Fuzzy Sets Syst., vol. 126, no. 2, pp. 137-155, 2002.
14. Q. Hu, L. Zhang, S. An, D. Zhang, and D. Yu, "On robust fuzzy rough set models," IEEE Trans. Fuzzy Syst., vol. 20, no. 4, pp. 636-651, Aug. 2012.
15. D. Chen, S. Kwong, Q. He, and H.Wang, "Geometrical interpretation and applications of membership functions with fuzzy rough sets," Fuzzy Sets Syst., vol. 193, pp. 122-135, 2012.
16. H. S. Seung, M. Opper, and H. Sompolinsky, "Query by committee," in Proc. 5th Annu. Workshop Comput. Learn. Theory, 1992, pp. 287-294.
17. J. Cheng and K.Wang, "Active learning for image retrievalwith co-SVM," Pattern Recog., vol. 40, no. 1, pp. 330-334, 2007.
18. Q. Hu, L. Zhang, D. Chen,W. Pedrycz, and D. Yu, "Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications," Int. J. Approx. Reason., vol. 51, no. 4, pp. 453-471, 2010.
19. J. C. Huhn and E. Hullermeier, "Fr3: A fuzzy rule learner for inducing reliable classifiers," IEEE Trans. Fuzzy Syst., vol. 17, no. 1, pp. 138-149, Feb. 2009.
20. E. Hüllermeier and K. Brinker, "Learning valued preference structures for solving classification problems," Fuzzy Sets Syst., vol. 159, no. 18, pp. 2337-2352, 2008.
21. C. Campbell, N. Cristianini, and A. Smola, "Query learning with large margin classifiers," in Proc. Int. Conf. Mach. Learn., 2000, pp. 111-118.
22. T. M. Mitchell, "Version spaces: An approach to concept learning," Defense Tech. Inf. Center, Fort Belvoir, VA, USA, Tech. Rep., 1978
23. S. S. Ho and H. Wechsler, "Query by transduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 9, pp. 1557-1571, Sep. 2008.