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Great Deluge Algorithm for Rough Set Attribute Reduction

  • Conference paper
Database Theory and Application, Bio-Science and Bio-Technology (BSBT 2010, DTA 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 118))

Abstract

Attribute reduction is the process of selecting a subset of features from the original set of features that forms patterns in a given dataset. It can be defined as a process to eliminate redundant attributes and at the same time is able to avoid any information loss, so that the selected subset is sufficient to describe the original features. In this paper, we present a great deluge algorithm for attribute reduction in rough set theory (GD-RSAR). Great deluge is a meta-heuristic approach that is less parameter dependent. There are only two parameters needed; the time to “spend” and the expected final solution. The algorithm always accepts improved solutions. The worse solution will be accepted if it is better than the upper boundary value or “level”. GD-RSAR has been tested on the public domain datasets available in UCI. Experimental results on benchmark datasets demonstrate that this approach is effective and able to obtain competitive results compared to previous available methods. Possible extensions upon this simple approach are also discussed.

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References

  1. Abdullah, S., Burke, E.K.: A Multi-start large neighbourhood search approach with local search methods for examination timetabling. In: International Conference on Automated Planning and Scheduling (ICAPS 2006), Cumbria, UK, pp. 334–337 (2006)

    Google Scholar 

  2. Burke, E.K., Bykov, Y., Newall, J.P., Petrovic, S.: A time-predefined local search approach to exam timetabling problem. IIE Transactions 36(6), 509–528 (2004)

    Article  Google Scholar 

  3. Dueck, G.: New Optimization Heuristics. The Great Deluge Algorithm and the Record-to-Record Travel. Journal of Computational Physics 104(1), 86–92 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  4. Duntsch, I., Gediga, G.: Uncertainty measures of rough set prediction. Artificial Intelligence 106(1), 109–137 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  5. Hedar, A., Wang, J., Fukushima, M.: Tabu search for attribute reduction in rough set theory. Technical Report 2006- 08, Department of Applied Mathematics and Physics, Kyoto University. Soft Computing 12(9), 909–918 (2006)

    MATH  Google Scholar 

  6. Jensen, R., Shen, Q.: Finding Rough set reducts with ant colony optimization. In: Proc. of 2003 UK Workshop Computational Intelligence, pp. 15–22 (2003)

    Google Scholar 

  7. Jensen, R., Shen, Q.: Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough Based Approaches. IEEE Transactions on Knowledge and Data Engineering 16(12), 1457–1471 (2004)

    Article  Google Scholar 

  8. Ke, L., Feng, Z., Ren, Z.: An efficient ant colony optimization approach to attribute reduction in rough set theory. Pattern Recognition Letters 29(9), 1351–1357 (2008)

    Article  Google Scholar 

  9. Landa-Silva, D., Obit, J.H.: Evolutionary Non-linear Great Deluge for University Course Timetabling. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS, vol. 5572, pp. 269–276. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. McMullan, P.: An extended implementation of the great deluge algorithm for course timetabling. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS Part I 2007. LNCS, vol. 4487, pp. 538–545. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  11. Pawlak, Z.: Rough sets. Internat. J. Comput. Inform. Sci. 11(5), 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  12. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer, Boston (1991)

    Book  MATH  Google Scholar 

  13. Turabieh, H., Abdullah, S., McCollum, B.: Electromagnetism-like Mechanism with Force Decay Rate Great Deluge for the Course Timetabling Problem. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds.) RSKT 2009. LNCS, vol. 5589, pp. 497–504. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  14. Turabieh, H., Abdullah, S., McCollum, B.: A hybridization of Electromagnetism-like Mechanism and Great Deluge for Examination Timetabling Problem. In: Blesa, M.J., Blum, C., Di Gaspero, L., Roli, A., Sampels, M., Schaerf, A. (eds.) HM. LNCS, vol. 5818, pp. 60–72. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Wang, J., Hedar, A., Zheng, G., Wang, S.: Scatter Search for Rough Set Attribute Reduction. International Joint Conference on Computational Sciences and Optimization 1, 531–535 (2009)

    Article  Google Scholar 

  16. WenXiu, Z., GuoFang, Q., WeiZhi, W.: A general approach to attribute reduction in rough set theory. Science in China Series F: Information Sciences 50(2), 188–197 (2007)

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Data Mining and Optimisation Research Group (DMO), Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Salwani Abdullah & Najmeh Sadat Jaddi

Authors
  1. Salwani Abdullah
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  2. Najmeh Sadat Jaddi
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Editor information

Editors and Affiliations

  1. Victoria University, 8001, Melbourne, VIC, Australia

    Yanchun Zhang

  2. University of Calabria, Via P. Bucci, 41C, I-87036, Rende, Cosenza, Italy

    Alfredo Cuzzocrea

  3. Hosei University, 3-7-2, Kajino-cho, Koganei-shi, 184-8584, Tokyo, Japan

    Jianhua Ma

  4. Information Security Infrastructure Research Group, Electronics and Telecommunications Research Institute, 161, Gajeong-Dong, Yuseong-Gu, Daejeon, Korea

    Kyo-il Chung

  5. Engineering and Electronics, Edinburgh University, King’s Buildings, Faraday, rm 3.101, Mayfield Road, EH9 3JL, Edinburgh, UK

    Tughrul Arslan

  6. Nanjing University of Aeronautics and Astronautics, 210016, Jiangsu, Nanjing, China

    Xiaofeng Song

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© 2010 Springer-Verlag Berlin Heidelberg

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Abdullah, S., Jaddi, N.S. (2010). Great Deluge Algorithm for Rough Set Attribute Reduction. In: Zhang, Y., Cuzzocrea, A., Ma, J., Chung, Ki., Arslan, T., Song, X. (eds) Database Theory and Application, Bio-Science and Bio-Technology. BSBT DTA 2010 2010. Communications in Computer and Information Science, vol 118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17622-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-17622-7_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17621-0

  • Online ISBN: 978-3-642-17622-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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