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Rough Set Theory for Feature Ranking of Traditional Malay Musical Instruments Sounds Dataset

  • Conference paper
Software Engineering and Computer Systems (ICSECS 2011)

Abstract

This paper presents an alternative feature ranking technique for Traditional Malay musical instruments sounds dataset using rough-set theory based on the maximum degree of dependency of attributes. The modeling process comprises seven phases: data acquisition, sound editing, data representation, feature extraction, data discretization, data cleansing, and finally feature ranking using the proposed technique. The results show that the selected features generated from the proposed technique able to reduce the complexity process.

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References

  1. Liu, M., Wan, C.: Feature Selection for Automatic Classification of Musical Instrument Sounds. In: Proceedings of the 1st ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2001, pp. 247–248 (2001)

    Google Scholar 

  2. Deng, J.D., Simmermacher, C., Cranefield, S.: A Study on Feature Analysis for Musical Instrument Classification. IEEE Transactions on System, Man, and Cybernetics-Part B: Cybernetics 38(2), 429–438 (2008)

    Article  Google Scholar 

  3. Benetos, E., Kotti, M., Kotropoulus, C.: Musical Instrument Classification using Non-Negative Matrix Factorization Algorithms and Subset Feature Selection. In: Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, vol. 5, pp. 221–224 (2006)

    Google Scholar 

  4. Pawlak, Z.: Rough Sets. International Journal of Computer and Information Science 11, 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  5. Banerjee, M., Mitra, S., Anand, A.: Feature Selection using Rough Sets. In: Banerjee, M., et al. (eds.) Multi-Objective Machine Learning. SCI, vol. 16, pp. 3–20 (2006)

    Google Scholar 

  6. Modrzejewski, M.: Feature Selection using Rough Sets Theory. In: Brazdil, P.B. (ed.) ECML 1993. LNCS, vol. 667, pp. 213–226. Springer, Heidelberg (1993)

    Chapter  Google Scholar 

  7. Li, H., Zhang, W., Xu, P., Wang, H.: Rough Set Attribute Reduction in Decision Systems. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2008. LNCS (LNAI), vol. 5097, pp. 132–141. Springer, Heidelberg (2008)

    Google Scholar 

  8. Herawan, T., Mustafa, M.D., Abawajy, J.H.: Rough set approach for selecting clustering attribute. Knowledge Based Systems 23(3), 220–231 (2010)

    Article  Google Scholar 

  9. Senan, N., Ibrahim, R., Nawi, N.M., Mokji, M.M.: Feature Extraction for Traditional Malay Musical Instruments Classification. In: Proceeding of International Conference of Soft Computing and Pattern Recognition, SOCPAR 2009, pp. 454–459 (2009)

    Google Scholar 

  10. Palaniappan, S., Hong, T.K.: Discretization of Continuous Valued Dimensions in OLAP Data Cubes. International Journal of Computer Science and Network Security 8, 116–126 (2008)

    Google Scholar 

  11. Pawlak, Z.: Rough set and Fuzzy sets. Fuzzy sets and systems 17, 99–102 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  12. Pawlak, Z., Skowron, A.: Rudiments of rough sets. Information Science 177(1), 3–27 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  13. Zhao, Y., Luo, F., Wong, S.K.M., Yao, Y.: A general definition of an attribute reduct. In: Yao, J., Lingras, P., Wu, W.-Z., Szczuka, M.S., Cercone, N.J., Ślęzak, D. (eds.) RSKT 2007. LNCS (LNAI), vol. 4481, pp. 101–108. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  14. Pawlak, Z.: Rough classification. International Journal of Human Computer Studies 51, 369–383 (1983)

    Article  Google Scholar 

  15. Warisan Budaya Malaysia: Alat Muzik Tradisional, http://malaysiana.pnm.my/kesenian/Index.htm

  16. Shriver, R.: Webpage, www.rickshriver.net/hires.htm

  17. Senan, N., Ibrahim, R., Nawi, N.M., Mokji, M.M., Herawan, T.: The Ideal Data Representation for Feature Extraction of Traditional Malay Musical Instrument Sounds Classification. In: Huang, D.-S., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds.) ICIC 2010. LNCS, vol. 6215, pp. 345–353. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

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Senan, N., Ibrahim, R., Mohd Nawi, N., Riyadi Yanto, I.T., Herawan, T. (2011). Rough Set Theory for Feature Ranking of Traditional Malay Musical Instruments Sounds Dataset. 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_45

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  • DOI: https://doi.org/10.1007/978-3-642-22191-0_45

  • 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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