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Similarity Approach on Fuzzy Soft Set Based Numerical Data Classification

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Software Engineering and Computer Systems (ICSECS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 180))

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Abstract

Application of soft sets theory for classification of natural textures has been successfully carried out by Mushrif et. al.. However the approach can not be applied in a particular classification problem, such as problem of text classification. In this paper, we propose the new numerical data classification based on similarity fuzzy soft sets. In addition can be applied to text classification, this new fuzzy soft sets classifier (FSSC) can also be used in general numerical data classification. As compare to previous soft sets classifier on seven real data sets experiments, the new proposed approach give high degree of accuracy with low computational complexity.

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References

  1. Aktas, H., Çagman, N.: Soft sets and soft groups. Inf. Sci., 2726–2735 (2007)

    Google Scholar 

  2. Ali, S., Smith, K.: On learning algorithm selection for classification, App. Soft Comp. 6, 119–138 (2006)

    Article  Google Scholar 

  3. Chen, D., Tsang, E., Yeung, D., Wang, X.: The parametrization reduction of soft sets and its applications. Comput. Math. Appl. 49, 757–763 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cai, D., Wang, X., He, X.: Probabilistic Dyadic Data Analysis with Local and Global Consistency. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 105–112 (2009)

    Google Scholar 

  5. Feng, F., Jun, Y.B., Liu, X., Li, L.: An adjustable approach to fuzzy soft set based decision making J. Comp. App. Math. 234, 10–20 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  6. Frank, A., Asuncion, A.: UCI Machine Learning Repository University of California, Irvine, School of Information and Computer Sciences (2010)

    Google Scholar 

  7. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update (2009)

    Google Scholar 

  8. Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2006)

    MATH  Google Scholar 

  9. Kharal, A.: Distance and Similarity Measures for Soft Sets. New Math. & Nat. Comp (NMNC) 06, 321–334 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  10. Kong, Z., Gao, L., Wang, L.: Comment on a fuzzy soft set theoretic approach to decision making problems. J. Comput. Appl. Math. 223, 540–542 (2009)

    Article  MATH  Google Scholar 

  11. Maji, P., Biswas, R., Roy, A.: Fuzzy soft sets. J. Fuzzy Math. 9(3), 589–602 (2001)

    MathSciNet  MATH  Google Scholar 

  12. Maji, P., Roy, A., Biswas, R.: An application of soft sets in a decision making problem. Comput. Math. Appl. 44, 1077–1083 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  13. Maji, P., Biswas, R., Roy, A.: Soft set theory. Comput. Math. Appl. 45, 555–562 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. Majumdar, P., Samanta, S.: Generalised fuzzy soft sets. J. Comp. Math. App. 59, 1425–1432 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  15. Majumdar, P., Samanta, S.: Similarity measure of soft sets. NMNC 04, 1–12 (2008)

    MathSciNet  MATH  Google Scholar 

  16. Molodtsov, D.: Soft set theory–First results. Comp. Math. App. 37, 19–31 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  17. Mushrif, M.M., Sengupta, S., Ray, A.K.: Texture classification using a novel, soft-set theory based classification algorithm. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3851, pp. 246–254. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  18. Olson, D., Delen, D.: Advanced Data Mining Techniques, 1st edn. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  19. Pawlak, Z.: Rough sets. Int. J. of Inform. Comput. Sci. 11, 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  20. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic, Boston (1991)

    Book  MATH  Google Scholar 

  21. Roy, A., Maji, P.: A fuzzy soft set theoretic approach to decision making problems. J. Comp. App. Math. 203, 412–418 (2007)

    Article  MATH  Google Scholar 

  22. Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 42–49. ACM, New York (1999)

    Google Scholar 

  23. Zadeh, L.: Fuzzy sets. Inform. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. University Tun Hussein Onn, Malaysia

    Bana Handaga & Mustafa Mat Deris

Authors
  1. Bana Handaga
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  2. Mustafa Mat Deris
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Editor information

Editors and Affiliations

  1. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang, Malaysia

    Jasni Mohamad Zain

  2. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Kuantan, Pahang, Malaysia

    Wan Maseri bt Wan Mohd

  3. Information Systems Department, King Saud University, 11543, Riyadh, Saudi Arabia

    Eyas El-Qawasmeh

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© 2011 Springer-Verlag Berlin Heidelberg

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Handaga, B., Mat Deris, M. (2011). Similarity Approach on Fuzzy Soft Set Based Numerical Data Classification. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22191-0_50

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  • DOI: https://doi.org/10.1007/978-3-642-22191-0_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22190-3

  • Online ISBN: 978-3-642-22191-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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