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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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
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